Frédéric Grandjean

Simon Blanchet

Jérôme Murienne

Michaël Stéphanie Boulêtreau

Ivan Paz-Vinas

Iris Lang

Paul Millet

Charlotte Veyssière

Géraldine Loot

Julien Cucherousset

Inference of local invasion pathways in two invasive crayfish species displaying contrasting genetic patterns

Elles se touchent toutes »

Avant-propos

Cette thèse de l'école doctorale SEVAB a été réalisée au Laboratoire Évolution & Diversité Biologique au sein de l'équipe AQUAECO. Elle a été financée par une bourse doctorale ATP Paz-Vinas pour leur contribution aux comités de thèse. Merci aux différents propriétaires de gravières de nous avoir donné l'accès aux plans d'eau (un merci tout particulier à la fédération de pêche 31 pour son accueil chaleureux) et un énorme merci à Serge Boutes pour sa disponibilité et l'accès au Golf de Téoula pour l'échantillonnage de plans d'eau et la préparation d'une expérimentation en mésocosmes. Merci aux différents membres de l'équipe AQUAECO et plus généralement du laboratoire EDB qui ont pu m'apporter leur aide quand j'en avais besoin. Merci aux stagiaires pour leur soutien, et sans qui une grande partie de ce travail n'aurait pas pu être réalisée en si peu de temps, pour le terrain, les expérimentations, et la joie des dissections et du broyage en sous-sol ! Merci donc à Becky, pour ta joie de vivre et ton aide précieuse pour toutes ses extractions d'ADN ; merci Little J. d'avoir toujours su associer rigueur et déconnades ; merci Jérémy d'avoir supporté l'odeur des écrevisses pendant 2 mois (presque) sans râler; merci Benoît pour ton soutien sans faille pendant ces longues journées passées au sous-sol et d'avoir su gérer les imprévus; merci aussi à Thibaut, Gary, ma ptite Camille Kloug, Bastien (il faut que je te rende l'atlas des écrevisses !!), Flavien, Elsa. Un énorme merci à Laetitia et merci Axelle d'avoir apporté le soleil dans le bureau 253 ! Je remercie évidemment le reste de l'équipe Cuche pour tous ces bons moments, depuis mon arrivée (Rémy, Libor !) et au long de ces trois années (merci Paul, Ivan, Xavier, Maud !) et spéciale dédicace à ma Tchikita Louna : hâte qu'on retourne sur ce petit chemin…qui sent la noisette…oh OOOh. Un énorme merci Charlotte (Evangelista) pour nos échanges de mails qui m'ont beaucoup reboosté au cours des trois années, tes conseils toujours pertinents et ton implication dans la relecture de mon manuscrit de thèse.

Je tiens à remercier tous les membres du plateau technique du laboratoire EDB, pour leur aide et tous les bons moments. Je suis heureuse de retirer de ces trois années, plus que des collègues de bureau ou de travail, de véritables amis. En particulier, merci Charlotte (Veyssière) pour les formations microsat, la fête de la musique, le chocolat, et surtout merci Merci aussi à l'école SEVAB de créer de belles rencontres :p même si tu m'as oublié dans la première version de tes remerciements, Bennychou, tu mérites ta place ici.

Je remercie aussi et évidemment le crew des post-doctorants et des doctorants du 4R1 : Isabel (pour ta joie de vivre, ta franchise du quotidien qui donne le sourire), Alexandre (pour le fun que tu as apporté dans ces 3 années et les buffalos !) , Jessica (pour les bons moments et ton aide précieuse en génétique), Kevin (pour tous ces petits bouts de chocolats, ces néologismes espagnols et ton aide en stats à mes débuts au labo) , Juan (pour ton optimisme communicatif et tes mots rassurants), Luana (pour ton calme, et tes petits pas de danse), Maëva (pour ta bonne humeur, ta présence, tes conseils en sac de couchage :p à quand la prochaine dégustation de gin ?), Maxime (pour ta sympathie et ta sagesse), Eglantine (pour les petites discussions des pauses, et on a bien déconné à Rennes !) , Eloïse (tu reviens manger un burger à la maison quand tu veux !), Sean (pour ton engouement à aller boire des coups et d'avoir accepté ma présence au bureau 26), Céline (oui je te mets dans les doctorants :p merci de m'avoir fait voyager avec tes histoires et photos d'Amérique du Sud), Allan (pour ton aide précieuse en stats à plusieurs reprises). Un grand merci également à E-Ping, Laura, Pauline, Sean, Opale, Guohuan, Seb, Marine, Lucie, Quentin, Camille, Thibaut.

Merci Sandra, coéquipière de bureau bourdonnante au milieu des poissons ! Merci à mes amis d'ailleurs pour leur patience, j'ai hâte de vous revoir ! Merci pour les skypes et les phonecalls de l'amitié à : Vassilia (le petit crâne mexicain ne m'a pas quitté de toute la thèse), le Rat parfois Chacal zonant dans les Lochs d'Ecosse qui se reconnaîtra, Paul fils du Big Chewbangcca, Théo. Spéciale dédicace aux Gladiatouzes qui m'ont beaucoup trop manqué ces trois années.

Merci à l'orchestre de La Vache et en particulier merci à Marie, il faudra perpétuer les apéros du mardi soir ! Merci au crew des Guuuuurls pour ces petits moments de vie qui sont du bonheur à l'état pur.

Merci aux meilleurs voisins du monde Charlotte et Steeve d'avoir égayé ces trois années et d'avoir entretenu mon quota de junkfood quasi hebdomadaire ! Merci à ma famille de m'avoir toujours laissé libre de mes choix professionnels, de m'avoir soutenue dans ces choix et d'avoir enfin intégré (pour certain-e-s ?) que je ne travaillais pas sur les crevettes.

Enfin merci à celle qui a su me supporter (dans tous les sens du termes), en particulier dans les moments difficiles, d'avoir accepté (et je sais que ça t'a coûté) les réveils aux aurores pendant le terrain et en fin de thèse. Merci pour tous ces beaux moments d'évasion à la montagne ou sur un air endiablé dans le salon. Vivement la traversée des Pyrénées ! Vivement la suite… [START_REF] Belfiore | Variable microsatellite loci in red swamp crayfish, Procambarus clarkii, and their characterization in other crayfish taxa[END_REF] and [START_REF] Jiang | Microsatellite marker identification from transcriptome derived sequences of the red swamp crawfish, Procambarus clarkii[END_REF] for Procambarus clarkii, and [START_REF] Jiang | Microsatellite marker identification from transcriptome derived sequences of the red swamp crawfish, Procambarus clarkii[END_REF] and [START_REF] Hulák | Cross-species amplification of microsatellite markers in the invasive spiny-cheek crayfish (Orconectes limosus): assessment and application[END_REF] for Faxonius limosus. ______________________ 106 [START_REF] Smith | Evolutionary significance of resource polymorphisms in fishes, amphibians, and birds[END_REF] and [START_REF] Lockwood | Invasion Ecology[END_REF]. __________________________________________________ 126 4 Frequency distribution of Procambarus clarkii body morphological scores obtained using a Discriminant Functional Analysis along the littoral-pelagic axis (nlittoral = 20, dark grey; npelagic = 20 except for lake J where npelagic = 17, blue) of the 7 gravel pit lakes. Note that the X-axis scale is different for Lake K. __________________________________________________ 146 Figure Appendix V.5 Stable isotopes values (δ 15 N and δ 13 C; ‰) of individuals Procambarus clarkii (circles) from littoral (dark grey) and pelagic (blue) habitats in the 7 gravel pit lakes. Black triangles and white squares represent periphyton and zooplankton in each lake, respectively. Note that the Y-axis scale for Lake K differs from the others. ____________________________ 147 (red) and Faxonius limosus (dark yellow) in lake Lamartine, calculated using catch per unit effort (CPUE) expressed in ind. trap -1 .hr -1 , on 9 occasions from June to December 2018. 36 baited traps (one cylindrical trap: 62cm x 34cm x 34cm, mesh size: 10 mm; one rectangular trap: 95cm x 20cm x 20cm, mesh size: 4 mm) were placed along transect lines, for one night (16h), and covered both littoral and pelagic habitats. _________________________________________________________________________________ [START_REF] Vellend | Connections between species diversity and genetic diversity[END_REF] et [START_REF] Marin | Biological invasion: the influence of the hidden side of the (epi)genome[END_REF]. ______________________

Table des matières

Liste des tables

Table III.S1 Populations of Faxonius limosus with information about lakes (Code, date of Creation, Latitude, Longitude and their level of fishery Management) and genetic analyses (sampling sizes (N), mean allelic richness (AR), expected heterozygosity (Hexp), mean private allelic richness (PA), mean genetic uniqueness (FstUNI) and mean Garza-Williamson statistic (GW)). A minimum sample size of 11 was considered for rarefaction procedures to obtain AR and PA estimates. The number of microsatellite loci (from a total of 8 polymorphic loci at the meta-population scale) monomorphic at the population level is also reported (NMONO). _______ Table III.S2 Populations of Procambarus clarkii with information about lakes (Code, date of Creation, Latitude, Longitude and their level of fishery Management) and genetic analyses (sampling sizes (N), mean allelic richness (AR), expected heterozygosity (Hexp), mean private allelic richness (PA), mean genetic uniqueness (FstUNI) and mean Garza-Williamson statistic (GW)). A minimum sample size of 12 was considered for rarefaction procedures to obtain AR and PA estimates. __________________________________________________________________ Table III.S3 Selected linear models explaining AR and PA values observed in Faxonius limosus.

No models with significant sources of variations were found for FstUNI for this species. Non-italic values correspond to p-values obtained through F-tests using the 'anova' function in R, while pvalues reported in italic correspond to p-values obtained through T-tests using the 'summary.lm' function in R (only reported for the factor variable Management and for the Intercept of models). Significant p-values are in bold. ______________________________________________________ Table III.S4 Best linear models (after a backward-selection procedure) explaining AR and FstUNI values observed in Procambarus clarkii. No models with significant sources of variations were found for PA for this species. Non-italic values correspond to p-values obtained through F-tests using the 'anova' function in R, while p-values reported in italic correspond to p-values obtained through T-tests using the 'summary.lm' function in R (only reported for the factor variable Management and for the Intercept of models). Significant p-values are in bold. ____________ Table IV.1 Environmental, historical and management characteristics of the 23 sampled lakes.

Table IV.S1

Genetic diversity of Faxonius limosus (based on 8 microsatellites) and Procambarus clarkii (based on 13 microsatellites) in the 11 lakes where the species co-occur. We quantified genetic diversity using allelic richness (AR), the mean number of alleles per locus (NA), and the fixation index (Fis) computed with with Fstat v2.9.3.2 [START_REF] Goudet | Fstat Vision (1.2): a computer program to calculate F-statistics[END_REF], and expected (Hexp) and observed (Hobs) heterozygosity, computed with Genetix v4.05 [START_REF] Belkhir | GENETIX 4.05, logiciel sous Windows TM pour la génétique des populations[END_REF]. _______ Table IV.S2 Results of the linear models testing the effect of Population and Sex on each phenotypic trait (PC1 and PC2 scores, carapace length, trophic position, terrestrial reliance, C:N:P ratios) for Procambarus clarkii (n = 501) and Faxonius limosus (n = 256). The full model included an interaction term (Sex x Population) which was removed from the final model if nonsignificant. Significant P values are in bold. ___________________________________________

Table IV.S3

Results of the linear mixed models testing the effect of environmental variables 1 and 2, and invaded time on each phenotypic trait (PC1 and PC2 scores, carapace length, trophic position, terrestrial reliance, C:N:P ratios) for Procambarus clarkii (n = 501) and Faxonius limosus (n = 256). The full model included double interaction terms which were removed using a backward procedure if non-significant. Significant P values are in bold. Increasing value for environmental variable 1 corresponds to increasing anthropogenic pressure, abundance of F. limosus and lake productivity and increasing value for environmental variable 2 corresponds to increasing predation pressure and decreasing abundance of P. clarkii. ___________________ 116 Table V.1 Genetic diversity of Procambarus clarkii in the littoral and pelagic habitats based on 14 microsatellites of 7 studied lakes. NA = mean number of alleles per locus, AR = allelic richness, He = expected heterozygosity, Ho = observed heterozygosity, FIS = fixation indices.132

Table Appendix

V.1 Environmental characteristics of the 16 sampled lakes (Haute-Garonne, France). Resource polymorphism was studied in 7 lakes (highlighted in bold) where sufficient number of Procambarus clarkii were collected in both habitats (mean number of individuals per habitat = 19.79 ± 0.8 SD). Distance pelagic traps was assessed by measuring the distance (in meters) perpendicularly to the shore with GIS (accuracy of GPS ± 5m). Predation pressure was not assessed in lake O this year. ____________________________________________________ 140 [START_REF] Belfiore | Variable microsatellite loci in red swamp crayfish, Procambarus clarkii, and their characterization in other crayfish taxa[END_REF] and [START_REF] Jiang | Microsatellite marker identification from transcriptome derived sequences of the red swamp crawfish, Procambarus clarkii[END_REF]. ____________ 142

Chapitre I

Introduction générale

Depuis les années 90 l'intérêt scientifique pour les relations entre biodiversité et fonctionnement des écosystèmes est grandissant [START_REF] Loreau | Biodiversity and ecosystem functioning: current knowledge and future challenges[END_REF][START_REF] Reiss | Emerging horizons in biodiversity and ecosystem functioning research[END_REF].

Dans le contexte actuel de crise de la biodiversité, il est d'autant plus important de comprendre ces relations. Les études à la fois théoriques et expérimentales ont démontré l'importance de la biodiversité sur la dynamique des écosystèmes [START_REF] Naeem | Declining biodiversity can alter the performance of ecosystems[END_REF][START_REF] Tilman | Biodiversity and stability in grasslands[END_REF][START_REF] Loreau | Biodiversity and ecosystem functioning : recent theoretical advances[END_REF][START_REF] Griffin | Biodiversity and the stability of ecosystem functioning[END_REF]. De manière générale, il est reconnu qu'une biodiversité importante augmente la productivité des écosystèmes, ce qui peut favoriser la stabilité des processus écologiques, et offre une meilleure résistance et résilience des écosystèmes aux perturbations d'origine naturelle ou anthropique [START_REF] Hooper | Effects of biodiversity on ecosystem functioning: a consensus of current knowledge[END_REF].

Un des mécanismes sous-jacents à cette capacité de résilience est la redondance fonctionnelle, c'est-à-dire la multiplicité d'espèces ayant des fonctions équivalentes dans l'écosystème [START_REF] Chapin | Biodiversity and ecosystem processes[END_REF][START_REF] Peterson | Ecological resilience, biodiversity, and scale[END_REF]. La redondance fonctionnelle permet donc de compenser la perte de certaines espèces par un effet tampon qui assure le maintien des processus écologiques au sein de l'écosystème perturbé [START_REF] Hooper | Effects of biodiversity on ecosystem functioning: a consensus of current knowledge[END_REF]. Ceci illustre la complexité de la notion de biodiversité et l'importance de ne pas considérer uniquement la biodiversité taxonomique ou phylogénique pour comprendre les relations entre biodiversité et fonctionnement des écosystèmes, mais de considérer également la biodiversité fonctionnelle [START_REF] Díaz | Functional diversity -at the crossroads between ecosystem functioning and environmental filters. Terrestrial ecosystems in a changing world[END_REF].

Variabilité intraspécifique

La complexité de la biodiversité réside également dans son organisation, puisqu'elle peut être mesurée à différents niveaux d'organisation biologique, allant du gène à l'écosystème.

Pendant longtemps la variabilité intraspécifique a été négligée au détriment de la variabilité interspécifique : autrement dit, tous les individus d'une même espèce étaient considérés comme écologiquement équivalents [START_REF] Díaz | Vive la différence: plant functional diversity matters to ecosystem processes[END_REF][START_REF] Lavorel | Predicting changes in community composition and ecosystem functioning from plant traits: revisiting the Holy Grail[END_REF]. Il est maintenant admis qu'au sein d'une même espèce les individus peuvent être spécialisés, c'est-à-dire occuper des niches écologiques différentes [START_REF] Bolnick | The ecology of individuals : incidence and implications of individual specialization[END_REF]. En conséquence, les individus d'une même espèce peuvent avoir des effets différents sur le fonctionnement et les dynamiques écologiques et évolutives parce qu'ils présentent des génotypes et/ou des phénotypes distincts [START_REF] Bolnick | The ecology of individuals : incidence and implications of individual specialization[END_REF][START_REF] Bolnick | Why intraspecific trait variation matters in ecology[END_REF].

Variabilité phénotypique : variations et covariations de traits

Darwin considérait que les variations intraspécifiques étaient d'origine aléatoire, et qu'elles pouvaient faire l'objet d'une sélection naturelle favorisant les individus avec les caractères les plus avantageux pour la survie, c'est-à-dire les individus avec la plus forte valeur sélective (fitness 1 en anglais ; [START_REF] Arnold | Morphology, performance and fitness[END_REF]. La valeur sélective dans un environnement donné mesure donc la capacité d'un génotype à contribuer à la génération suivante et dépend de la survie, de la croissance et de la fécondité des individus. Ces propriétés, ainsi que toutes les caractéristiques morphologiques, physiologiques, phénologiques et comportementales des individus sont appelées traits, et forment le phénotype des individus [START_REF] Bolnick | The ecology of individuals : incidence and implications of individual specialization[END_REF][START_REF] Violle | Let the concept of trait be functional ![END_REF]. La variabilité phénotypique correspond donc aux variations de traits entre individus d'une même espèce. Quand les traits traduisent les performances écologiques des individus et ainsi leur valeur sélective, ils sont qualifiés de traits fonctionnels [START_REF] Mcgill | Rebuilding community ecology from functional traits[END_REF][START_REF] Violle | Let the concept of trait be functional ![END_REF]. Les traits de réponse traduisent la réponse des organismes à des variations environnementales et sont à distinguer des traits d'effet qui décrivent l'effet des individus sur le fonctionnement de l'écosystème dont ils font partie [START_REF] Violle | The return of the variance: intraspecific variability in community ecology[END_REF][START_REF] Díaz | Functional traits, the phylogeny of function, and ecosystem service vulnerability[END_REF]. Certains traits sont à la fois considérés comme des traits de réponse et d'effet au regard des questions de recherche soulevées [START_REF] Díaz | Functional traits, the phylogeny of function, and ecosystem service vulnerability[END_REF]. C'est par exemple le cas des traits dits stoechiométriques 2 , qui caractérisent la composition élémentaire corporelle des organismes (e.g. ratios Carbone:Azote:Phosphore, noté C:N:P; [START_REF] Leal | The ecology and evolution of stoichiometric phenotypes[END_REF]. Les traits stoechiométriques peuvent par exemple refléter le régime alimentaire et l'allocation des nutriments selon le stade de développement des organismes (trait de réponse; [START_REF] Vrede | Ecological stoichiometry of Eurasian perchintraspecific variation due to size, habitat and diet[END_REF], ou encore les taux d'excrétion des individus qui affectent la disponibilité des nutriments dans le milieu pour les autres organismes (trait d'effet;[START_REF] Vanni | Predicting nutrient excretion of aquatic animals with metabolic ecology and ecological stoichiometry: a global synthesis[END_REF].

Il existe des intercorrélations entre les traits fonctionnels au sein des individus (autrement appelées covariation, intégration ou syndrome phénotypiques), c'est-à-dire que les valeurs de traits dépendent des valeurs d'autres traits au sein d'un individu. Le polymorphisme de ressource, à savoir l'existence de variations d'utilisation des ressources spatiales (i.e. l'habitat) ou trophiques associées à des morphologies différentes des individus, constitue un exemple très simple de covariations de traits [START_REF] Smith | Evolutionary significance of resource polymorphisms in fishes, amphibians, and birds[END_REF]. Les covariations phénotypiques ont principalement fait l'objet d'études cherchant à expliquer l'interdépendance du comportement et des traits physiologiques des organismes (Careau et 1 Dans le manuscrit sont précisés les termes anglais communément utilisés par les écologues francophones. 2 La stoechiométrie correspond à la composition élémentaire corporelle des organismes (e.g. proportions de carbone, azote, phosphore et ratios entre ces éléments). al., 2008;[START_REF] Biro | Do consistent individual differences in metabolic rate promote consistent individual differences in behavior?[END_REF][START_REF] Reale | Personality and the emergence of the pace-of-life syndrome concept at the population level[END_REF][START_REF] Dingemanse | Defining behavioural syndromes and the role of "syndrome deviation" in understanding their evolution[END_REF]. Ces covariations phénotypiques sont autant amenées à changer dans les populations naturelles sous l'effet de la sélection et de la plasticité, que les moyennes de traits et leurs variances [START_REF] Pigliucci | Phenotypic integration: studying the ecology and evolution of complex phenotypes[END_REF], et elles traduisent à la fois les contraintes environnementales et les contraintes ontogénétiques propre aux organismes [START_REF] Murren | The integrated phenotype[END_REF][START_REF] Armbruster | Integrated phenotypes: understanding trait covariation in plants and animals[END_REF][START_REF] Laughlin | Fitness of multidimensional phenotypes in dynamic adaptive landscapes[END_REF]. Tout comme les valeurs moyennes et les variances de traits, les covariations de traits varient donc entre espèces (variation interspécifique) mais également au sein d'une même espèce (variation intraspécifique ; [START_REF] Blanck | Large-scale intraspecific variation in life-history traits of European freshwater fish[END_REF][START_REF] Peiman | Comparative analyses of phenotypic trait covariation within and among populations[END_REF]Raffard et al., 2019a).

Le cadre conceptuel le plus utilisé au cours des dernières années pour caractériser les covariations phénotypiques est sûrement celui de l'hypothèse du syndrome du rythme de vie (Pace-of-lice syndrome ou POLS en anglais; [START_REF] Reale | Personality and the emergence of the pace-of-life syndrome concept at the population level[END_REF][START_REF] Dammhahn | Pace-of-life syndromes: a framework for the adaptive integration of behaviour, physiology and life history[END_REF]. Cette hypothèse est fondée sur l'idée que les traits d'histoire de vie des individus (i.e. croissance, survie, reproduction) ainsi que leurs traits physiologiques, comportementaux et morphologiques ont co-évolué sous l'effet des contraintes environnementales. La connaissance des relations entre traits, et donc des compromis entre les différentes fonctions des organismes et de leurs contraintes physiologiques rend possible (i) la prédiction de valeurs de traits basée sur un nombre limité de traits mesurés et (ii) l'inférence des effets des individus sur le fonctionnement de l'écosystème, autrement dit, l'intégration fonctionnelle [START_REF] Armbruster | Integrated phenotypes: understanding trait covariation in plants and animals[END_REF]. C'est dans cette deuxième optique que Raffard et al. (2017) ont développé le concept du syndrome fonctionnel, pour une compréhension plus intégrative des effets des individus sur le fonctionnement des écosystèmes. Le syndrome fonctionnel se définit comme l'association d'une suite de traits de réponse (syndrome de réponse) et de traits d'effet (syndrome d'effet) corrélés entre eux, respectivement (Raffard et al., 2017). Dans cette étude, des traits physiologiques comme le métabolisme (e.g. consommation d'oxygène) et la stoechiométrie des individus semblent être les principaux facteurs expliquant les covariations entre traits et entre syndromes de réponse et d'effet.

Processus évolutifs et déterminants écologiques de la variabilité intraspécifique

La variabilité phénotypique présentée par les individus d'une même espèce peut souligner des différences génétiques entre ces individus. La variabilité génétique d'une population est façonnée par des flux de gènes et se traduit en général par sa richesse et sa fréquence allélique 3 . Actuellement il est accepté que la variabilité génétique d'une population résulte de l'histoire démographique des individus considérés, ainsi que de processus évolutifs tels que (i) les mutations qui permettent la formation de nouveaux allèles, (ii) la migration qui entraîne des flux de gènes, (iii) la dérive génétique et (iv) la sélection qui conduisent à la perte ou à la fixation d'allèles, de manière aléatoire ou non, respectivement [START_REF] Freeland | Molecular ecology[END_REF] Box 1).

Box 1

Forces évolutives

Les mutations sont des événements ponctuels augmentant la variabilité génétique qui sont reconnus pour être majoritairement neutres vis-à-vis de la valeur sélective des individus.

Leur maintien dans les populations sera déterminé par une combinaison entre hasard et sélection [START_REF] Freeland | Molecular ecology[END_REF].

La migration est souvent liée à la dispersion d'individus entre populations qui peut entraîner des flux de gènes si les individus produisent une descendance viable. Les flux de gènes augmentent la diversité génétique d'une population mais tendent à homogénéiser les populations entre elles.

La dérive génétique correspond à l'évolution aléatoire des fréquences alléliques dans une population, indépendamment des mutations et des flux de gènes. C'est une force évolutive très marquée dans les populations isolées et de petit effectif, pouvant conduire à une perte de diversité génétique de ces populations par la fixation et/ou la perte d'allèles [START_REF] Hartl | Principles of population genetics[END_REF]. À long terme, la dérive génétique peut entraîner des différenciations génétiques et phénotypiques entre populations [START_REF] Rogell | The effects of selection, drift and genetic variation on life-history trait divergence among insular populations of natterjack toad, Bufo calamita[END_REF].

La sélection constitue un autre processus adaptatif clef des dynamiques éco-évolutives4 qui affecte directement les phénotypes indépendamment des génotypes associés. La variabilité génétique y est indirectement soumise, par sa relation aux traits phénotypiques affectant la valeur sélective des individus (Hendry, 2016). La sélection permet une adaptation locale des meilleurs phénotypes par une maximisation de la valeur sélective des individus dans un environnement donné. Les phénotypes sélectionnés sont donc fortement dépendants des conditions biotiques et abiotiques locales, et seraient moins performants dans d'autres conditions environnementales.

Les contraintes environnementales comme l'isolement géographique de la population (éloignement, ou barrière de dispersion d'individus) peuvent limiter les flux de gènes et façonner la variabilité génétique des populations [START_REF] Manel | Landscape genetics: combining landscape ecology and population genetics[END_REF]. Les contraintes environnementales peuvent également entraîner un changement de phénotype sans changement de génotype appelé plasticité phénotypique, qui confère une capacité adaptative aux individus [START_REF] Bradshaw | Evolutionary significance of phenotypic plasticity in plants[END_REF]. La plasticité phénotypique offre donc une rapidité de réponse (e.g. comportementale, physiologique, alimentaire, morphologique) des individus, ce qui la rend essentielle à court terme, en particulier dans le contexte de changement global [START_REF] Aitken | Adaptation, migration or extirpation: climate change outcomes for tree populations[END_REF][START_REF] Matesanz | Global change and the evolution of phenotypic plasticity in plants[END_REF][START_REF] Caruso | Widespread rapid reductions in body size of adult salamanders in response to climate change[END_REF]. Il est important de souligner que s'il est généralement reconnu que la plasticité phénotypique confère une capacité d'adaptation aux individus, elle ne favorise pas toujours une augmentation de la valeur sélective, par exemple dans le cas de gros écarts fréquents de conditions environnementales (e.g. plasticité neutre ou mal-adaptative ; [START_REF] Ghalambor | Adaptive versus nonadaptive phenotypic plasticity and the potential for contemporary adaptation in new environments[END_REF]. La plasticité phénotypique peut également résulter de l'interaction gènes x environnement, c'est-à-dire que la différence entre deux phénotypes produits par deux génotypes différents varie en fonction des conditions environnementales. Des mécanismes relevant du contrôle endocrinien ou encore de l'épigénétique peuvent expliquer cette interaction [START_REF] Nijhout | Development and evolution of adaptive polyphenisms[END_REF][START_REF] Vogt | Facilitation of environmental adaptation and evolution by epigenetic phenotype variation : insights from clonal , invasive , polyploid , and domesticated animals[END_REF].

Les déterminants des covariations de traits restent à ce jour peu compris [START_REF] Peiman | Comparative analyses of phenotypic trait covariation within and among populations[END_REF][START_REF] Diaz Pauli | Ecosystem consequences of multi-trait response to environmental changes in Japanese medaka, Oryzias latipes[END_REF]. Une intégration génétique codant pour les traits [START_REF] Via | Back to the future: genetic correlations, adaptation and speciation[END_REF][START_REF] Jones | Epistasis and natural selection shape the mutational architecture of complex traits[END_REF], des réponses plastiques similaires ou différenciées de certains traits [START_REF] Schlichting | Phenotypic integration and environmental change: what are the consequences of differential phenotypic plasticity of traits ?[END_REF] ou encore des pressions de sélection favorisant certaines combinaisons de traits [START_REF] Donovan | The evolution of the worldwide leaf economics spectrum[END_REF][START_REF] Taff | Multimodal sexual selection in a warbler: plumage and song are related to different fitness components[END_REF] vont définir le nombre et l'intensité des covariations de traits d'un individu. Peu d'études se sont attachées à élucider la part de ces différents mécanismes dans la formation et le maintien des covariations de traits. Ces covariations procurent une capacité adaptative aux organismes, puisqu'elles leur confèrent la capacité de changer de phénotype de manière cohérente grâce à l'interdépendance des traits. En revanche, un fort syndrome fonctionnel peut traduire une faible plasticité phénotypique, et par conséquent limiter les individus à des conditions environnementales restreintes [START_REF] Gianoli | Phenotypic integration may constrain phenotypic plasticity in plants[END_REF].

Les patrons de variabilité génétique et phénotypique résultent donc à la fois de processus neutres impliquant le hasard (dérive, mutation, migration) et de processus adaptatifs (sélection, plasticité phénotypique) au regard de l'évolution. Il est complexe de mesurer l'héritabilité de nombreux traits dans les populations en milieu naturel, c'est-à-dire leur part de variation due à des effets génétiques. En conséquence la variabilité génétique « neutre » est souvent utilisée pour estimer le potentiel adaptatif des populations ou des individus [START_REF] Frankham | Introduction to conservation genetics[END_REF]. La comparaison des différences génétiques neutres (mesurées avec des marqueurs génétiques de type microsatellites 5 par exemple) et des différences phénotypiques (pour des traits quantitatifs comme la taille du corps ou la position trophique par exemple) permet donc d'estimer les importances relatives des processus neutres et des processus adaptatifs dans la différenciation des individus ou des populations, sans différencier la sélection et la plasticité [START_REF] Leinonen | Contrasting patterns of body shape and neutral genetic divergence in marine and lake populations of threespine sticklebacks[END_REF][START_REF] Brommer | Whither Pst? The approximation of Qst by Pst in evolutionary and conservation biology[END_REF][START_REF] Merilä | Climate change, adaptation, and phenotypic plasticity: the problem and the evidence[END_REF].

Variabilité intraspécifique et fonctionnement des écosystèmes

Les conséquences de la variabilité intraspécifique sur la structure des communautés et le fonctionnement des écosystèmes sont de plus en plus reconnues et étudiées (Des Roches et al., 2017;Raffard et al., 2019b). D'une manière générale la variabilité génétique a surtout été considérée pour son importance dans les processus évolutifs. Cependant, la variabilité génétique au sein des espèces est également reconnue pour avoir des conséquences au niveau des populations mais aussi à des échelles supérieures (e.g. communautés et écosystèmes) qui sont appelées phénotypes étendus en opposition au phénotype 'traditionnel' dont nous avons déjà parlé dans cette introduction (extended phenotypes en anglais; [START_REF] Dawkins | The extended phenotype[END_REF][START_REF] Whitham | Community and ecosystem genetics: a consequence of the extended phenotype[END_REF]. Les potentielles conséquences de la variabilité génétique peuvent être directes ou indirectes (Figure I.1). Par exemple, des génotypes différents au sein d'une espèce de plantes peuvent avoir des conséquences différentes sur les cycles biogéochimiques du carbone et de l'azote, et par extension sur les processus de décomposition de la litière [START_REF] Madritch | Phenotypic diversity influences ecosystem functioning in an oak sandhills community[END_REF][START_REF] Schweitzer | The interaction of plant genotype and herbivory decelerate leaf litter decomposition and alter nutrient dynamics[END_REF][START_REF] Schweitzer | Forest gene diversity is correlated with the composition and function of soil microbial communities[END_REF][START_REF] Rudman | Adaptive genetic variation mediates bottom-up and top-down control in an aquatic ecosystem[END_REF]. Intuitivement, la variabilité génétique a principalement des effets indirects sur le fonctionnement des écosystèmes, à travers les phénotypes qu'elle façonne. La variabilité génétique des traits écologiquement importants chez une espèce peut donc avoir un rôle notable sur le fonctionnement de l'écosystème. [START_REF] Hughes | Ecological consequences of genetic diversity[END_REF] soulignent également que « la variabilité intraspécifique peut être équivalente à la variabilité interspécifique dans des écosystèmes dominés par une ou très peu d'espèces, ou encore si la variabilité génétique de l'espèce considérée affecte la distribution et l'abondance d'une espèce dite « clef de voûte », c'est-à-dire une espèce qui a un effet disproportionné sur son environnement par rapport à son effectif ou sa biomasse » [START_REF] Paine | A conversation on refining the concept of keystone species[END_REF][START_REF] Crawford | Host-plant genotypic diversity mediates the distribution of an ecosystem engineer[END_REF].

5 Séquences courtes d'ADN (motifs de nucléotides) répétées en tandem qui sont parmi les marqueurs neutres les plus utilisés en génétique des populations [START_REF] Balloux | The estimation of population differentiation with microsatellite markers[END_REF][START_REF] Selkoe | Microsatellites for ecologists: A practical guide to using and evaluating microsatellite markers[END_REF]. Les approches écologiques basées sur les traits sont de plus en plus utilisées pour étudier les liens entre biodiversité et fonctionnement des écosystèmes [START_REF] Bolnick | Why intraspecific trait variation matters in ecology[END_REF][START_REF] Cadotte | Beyond species: functional diversity and the maintenance of ecological processes and services[END_REF][START_REF] Matthews | Under niche construction: an operational bridge between ecology, evolution, and ecosystem science[END_REF][START_REF] Violle | The emergence and promise of functional biogeography[END_REF], et sont d'autant plus pertinentes lorsqu'elles se concentrent sur des traits d'effet. Les effets de la variabilité intraspécifique peuvent être tout aussi forts que l'effet de l'ajout ou le retrait d'une espèce dans l'écosystème, d'autant plus si les variations interindividuelles considérées relèvent de traits particulièrement importants au regard des processus écosystémiques (Des Roches et al., 2017). Il est généralement accepté que l'intensité des effets des individus sur les processus écosystémiques est fortement dépendante de la taille des organismes [START_REF] Woodward | Body size in ecological networks[END_REF] et de leur métabolisme [START_REF] Brown | Toward a metabolic theory of ecology[END_REF]. Si les différences fonctionnelles entre individus sont faibles, alors c'est plutôt l'abondance ou la biomasse des organismes qui prédira les impacts des individus sur le fonctionnement de l'écosystème que la variabilité intraspécifique [START_REF] Wong | Trait-based ecology of terrestrial arthropods[END_REF]. Les traits décrivant la niche trophique des individus permettent d'appréhender leur implication dans les flux de nutriments et d'énergie au sein de la chaîne alimentaire. La dynamique de cette chaine alimentaire est également régulée par des mécanismes descendants et ascendants qui constituent des processus clefs de l'écosystème. Les cascades trophiques (effets descendants, top-down en anglais) traduisent l'impact des individus de niveau trophique supérieur sur les niveaux inférieurs [START_REF] Shurin | All wet or dried up? Real differences between aquatic and terrestrial food webs[END_REF]. Il existe aussi des effets ascendants (bottom-up en anglais) qui résultent de la

Flux de gènes

Dérive génétique Sélection

Mutations

Plasticité

Covariation de traits disponibilité en ressources et/ou nutriments qui affectent la biomasse des niveaux trophiques supérieurs [START_REF] Shurin | All wet or dried up? Real differences between aquatic and terrestrial food webs[END_REF]. Les traits stoechiométriques de feuilles de peuplier peuvent par exemple affecter les interactions entre plantes, insectes herbivores et oiseaux insectivores : le taux de consommation et la préférence des oiseaux pour certains individus dépend de la stoechiométrie des feuilles consommées par les insectes [START_REF] Müller | Tri-trophic effects of plant defenses: chickadees consume caterpillars based on host leaf chemistry[END_REF].

D'une manière générale, la stoechiométrie des organismes peut impacter les cycles biogéochimiques du carbone, du phosphore et de l'azote [START_REF] Leal | The ecology and evolution of stoichiometric phenotypes[END_REF][START_REF] Welti | Bridging food webs, ecosystem metabolism, and biogeochemistry using ecological stoichiometry theory[END_REF].

Une étude a montré que la stoechiométrie des consommateurs primaires peut affecter les taux de décomposition de la litière à travers les communautés microbiennes [START_REF] Hawlena | Fear of predation slows plant-litter decomposition[END_REF] et par extension, affecter la biodisponibilité des nutriments dans le milieu. Souvent, les processus écologiques de l'écosystème sont prédits par l'association de différentes valeurs de traits.

Nous avons vu plus haut que les traits de réponse, au travers de corrélations avec les traits d'effets, peuvent également affecter l'intensité et la nature des processus écosystémiques induits par les organismes. A l'aide d'une modélisation bioénergétique, Raffard et al. (2017) ont montré que des variations de syndrome réponse chez l'écrevisse de Louisiane, Procambarus clarkii, pouvaient modifier les taux de décomposition de litière par les écrevisses avec la même ampleur que des variations importantes de taille de population. D'avantage d'études incluant des approches multi-traits sont nécessaires à l'avenir pour mieux comprendre les implications des covariations de traits sur le fonctionnement des écosystèmes. En particulier, une meilleure connaissance des syndromes fonctionnels entre populations de même espèce (Raffard et al., 2019a) mais également entre espèces qui coexistent permettrait de prévoir les conséquences de la variabilité intraspécifique sur les structures de communautés et le fonctionnement des écosystèmes.

Invasions biologiques

Multiplication des invasions biologiques dans le contexte de changement global

Les invasions biologiques constituent une des principales causes d'érosion de la biodiversité mondiale, avec la destruction et la perte d'habitat [START_REF] Vitousek | Introduced species: a significant component of human-caused global change[END_REF][START_REF] Sala | Global biodiversity scenarios for the year 2100[END_REF][START_REF] Brook | Synergies among extinction drivers under global change[END_REF]. Le processus d'invasion, qui conduit à considérer une espèce non native comme invasive 6 , se compose d'une succession d'étapes au cours desquelles les individus exotiques sont filtrés au travers de barrières géographique, environnementale, reproductive et de dispersion [START_REF] Richardson | Naturalization and invasion of alien plants: concepts and definitions[END_REF]Blackburn et al., 2011) [START_REF] Lockwood | Invasion Ecology[END_REF]Blackburn et al., 2011). L'introduction d'espèces peut être délibérée (e.g. plantes ou animaux d'ornementation, cultures) ou accidentelle (e.g.

échappements, eaux de ballast, plantes obsidionales). Dans le contexte de globalisation des échanges mondiaux, les introductions d'espèces hors de leur aire de répartition naturelle se sont multipliées et accélérées au cours des dernières années [START_REF] Lockwood | Invasion Ecology[END_REF][START_REF] Gozlan | Introduction of non-native freshwater fish: is it all bad?[END_REF][START_REF] Seebens | No saturation in the accumulation of alien species worldwide[END_REF].

6 Dans la législation française le terme utilisé est « espèce exotique envahissante (EEE) ».

Vulnérabilité des écosystèmes dulçaquicoles face aux invasions biologiques

Les milieux aquatiques sont particulièrement vulnérables et sujets aux invasions biologiques [START_REF] Sala | Global biodiversity scenarios for the year 2100[END_REF][START_REF] García-Berthou | Introduction pathways and establishment rates of invasive aquatic species in Europe[END_REF]. Ceci est en partie attribuable à la grande capacité de dispersion des organismes aquatiques par rapport aux organismes terrestres [START_REF] Beisel | The elusive model of a biological invasion process: time to take differences among aquatic and terrestrial ecosystems into account[END_REF], mais également à l'urbanisation et aux activités humaines qui sont souvent liées à la proximité des étendues d'eau, maximisant les perturbations d'origine anthropique des milieux aquatiques [START_REF] Carpio | Angling as a source of non-native freshwater fish: a European review[END_REF]. Or, dans les écosystèmes perturbés, les opportunités de contamination des milieux par des espèces non natives sont décuplées [START_REF] Ricciardi | Facilitative interactions among aquatic invaders: is an "invasional meltdown" occurring in the Great Lakes?[END_REF][START_REF] Ross | Landscape determinants of nonindigenous fish invasions[END_REF]. De plus, une grande partie des espèces invasives aquatiques a été introduite délibérément pour des activités commerciales (aquaculture) et de loisir (pêche et aquariophilie) principalement. [START_REF] Pimentel | Update on the environmental and economic costs associated with alien-invasive species in the United States[END_REF] ont estimé que les coûts liés aux espèces invasives aquatiques aux États-Unis, prenant en compte les dégâts et pertes qu'elles engendrent et le coût de leur contrôle, dépassaient les 5.4 milliards de dollars annuels 7 . En Europe, les espèces invasives aquatiques coûtent près de 2.2 milliards d'euros par an [START_REF] Keller | Invasive species in Europe: ecology, status, and policy[END_REF]. Malgré une prise de conscience progressive au niveau mondial (Conventions de Rome 1952, Ramsar 1971, Washington 1973, Berne 1979, Rio 1992

La variabilité intraspécifique dans les invasions biologiques

Facteurs de succès d'invasion

Le succès des espèces invasives s'explique par de nombreux facteurs pouvant être externes (e.g. écosystèmes perturbés, ou communautés faiblement diversifiées), ou inhérents aux individus invasifs (e.g. forte plasticité phénotypique). La pression de propagules, à savoir le nombre initial d'individus introduits dans un environnement non natif, est un premier facteur déterminant du succès des espèces invasives [START_REF] Colautti | Propagule pressure: a null model for biological invasions[END_REF][START_REF] Jeschke | Determinants of vertebrate invasion success in Europe and North America[END_REF].

Intuitivement, plus la pression de propagules est grande plus les chances de succès d'invasion sont élevées. La pression de propagules est souvent associée aux traits des individus invasifs, que l'introduction soit volontaire (i.e. traits sélectionnés) ou non (i.e. traits traduisant la propension des individus introduits pour la survie [START_REF] Ricciardi | Recent mass invasion of the North American Great Lakes by Ponto-Caspian species[END_REF][START_REF] Cassey | Global patterns of introduction effort and establishment success in birds[END_REF]Juette et al., 2014). Il est reconnu que les organismes invasifs partagent un certain nombre de traits qui les rendent plus compétitifs vis-à-vis des organismes indigènes, pouvant ainsi expliquer leur succès de colonisation. Ces traits sont souvent associés à la dispersion, à la reproduction [START_REF] Deacon | How reproductive ecology contributes to the spread of a globally invasive fish[END_REF], ou au comportement des individus invasifs [START_REF] Sol | Behavioural flexibility and invasion success in birds[END_REF][START_REF] Suarez | The role of opportunity in the unintentional introduction of nonnative ants[END_REF]Juette et al., 2014). Les individus invasifs sont également souvent caractérisés par une meilleure acquisition des ressources [START_REF] Polo-Cavia | Aggressive interactions during feeding between native and invasive freshwater turtles[END_REF][START_REF] Mathakutha | Invasive species differ in key functional traits from native and non-invasive alien plant species[END_REF], ainsi qu'un régime alimentaire plutôt généraliste et une plus grande tolérance aux conditions abiotiques [START_REF] Moyle | Predicting invasion success: freshwater fishes in California as a model[END_REF].

Une grande variabilité phénotypique peut donc faciliter la naturalisation d'une espèce nouvellement introduite [START_REF] Forsman | Effects of genotypic and phenotypic variation on establishment are important for conservation, invasion, and infection biology[END_REF].

7 Les chiffres présentés ici sont déjà compensés par les bénéfices annuels attribuables aux activités de pêches impliquant les espèces invasives (e.g. 69 milliards de dollars annuels aux États-Unis ; [START_REF] Pimentel | Update on the environmental and economic costs associated with alien-invasive species in the United States[END_REF]. Idem pour les coûts européens.

La plasticité phénotypique confère une capacité d'adaptation et ainsi une plus forte probabilité de succès aux espèces invasives qui font souvent face à des contraintes environnementales différentes de celles présentes dans leur aire d'origine. Les traits des individus introduits/invasifs sont donc en général rapidement soumis à de fortes pressions de sélection. En conséquence, les phénotypes des individus invasifs peuvent évoluer peu de temps après leur introduction [START_REF] Kinnison | Population-specific variation in body dimensions of adult chinook salmon (Oncorhynchus tshawytscha) from New Zealand and their source population, 90 years after introduction[END_REF][START_REF] Huey | Rapid evolution of a geographic cline in size in an introduced fly[END_REF][START_REF] Gibert | Drosophila as models to understand the adaptive process during invasion[END_REF]. Même si une grande plasticité phénotypique caractérise certaines espèces invasives, ce n'est pas un facteur attribuable au succès d'invasion de toutes les espèces [START_REF] Richardson | Plant invasions: merging the concepts of species invasiveness and community invasibility[END_REF][START_REF] Davidson | Do invasive species show higher phenotypic plasticity than native species and, if so, is it adaptive? A meta-analysis[END_REF]. Lorsque la plasticité phénotypique est associée à un fort potentiel adaptatif, les chances de succès d'invasion sont augmentées [START_REF] Lee | Evolutionary genetics of invasive species[END_REF]. Une variabilité génétique élevée de l'espèce invasive constitue de ce fait un autre facteur de succès dans le contexte des invasions biologiques [START_REF] Lavergne | Increased genetic variation and evolutionary potential drive the success of an invasive grass[END_REF][START_REF] Rius | How important is intraspecific genetic admixture to the success of colonising populations?[END_REF][START_REF] Garnas | Complex patterns of global spread in invasive insects: eco-evolutionary and management consequences[END_REF]. Les mélanges génétiques (admixture) permettent d'augmenter la variance génétique des populations et potentiellement d'améliorer la valeur sélective des individus dans les environnements nouvellement colonisés [START_REF] Keller | History, chance and adaptation during biological invasion: separating stochastic phenotypic evolution from response to selection[END_REF][START_REF] Verhoeven | Population admixture, biological invasions and the balance between local adaptation and inbreeding depression[END_REF]Dufresnes et al., 2017). En revanche, dans certaines situations les mélanges génétiques entraînent plutôt une homogénéisation des populations non favorable au succès d'invasion car elle réduit alors la capacité des individus à s'adapter à de nouveaux environnements [START_REF] Spielman | Most species are not driven to extinction before genetic factors impact them[END_REF]

La variabilité intraspécifique porteuse de l'histoire d'invasion

Tout au long des invasions biologiques, les différentes forces évolutives présentées dans la première partie de cette introduction agissent pour façonner la variabilité génétique et la variabilité phénotypique des populations invasives [START_REF] Lee | Evolutionary genetics of invasive species[END_REF][START_REF] Keller | History, chance and adaptation during biological invasion: separating stochastic phenotypic evolution from response to selection[END_REF]. Les espèces invasives constituent donc une opportunité pour l'étude des processus écologiques et évolutifs contemporains [START_REF] Huey | Using invasive species to study evolution: case studies with Drosophila and Salmon. Species invasions: insights into ecology, evolution and biogeography[END_REF][START_REF] Sax | Ecological and evolutionary insights from species invasions[END_REF][START_REF] Moran | Evolutionary responses to global change: lessons from invasive species[END_REF]Hendry, 2016) [START_REF] Excoffier | Genetic consequences of range expansions[END_REF][START_REF] Bock | What we still don't know about invasion genetics[END_REF]. La dérive génétique peut alors entraîner une réduction supplémentaire de l'hétérozygotie dans cette petite fraction d'individus. Cette diminution de variabilité génétique inhérente à l'introduction d'un petit nombre d'individus peut augmenter la consanguinité (inbreeding depression en anglais), c'est-à-dire la réduction de la valeur sélective de la population due à la reproduction d'individus apparentés [START_REF] Frankham | Introduction to conservation genetics[END_REF]. En conséquence, la fréquence des allèles délétères augmente et le risque d'extinction de la population est accru. Le paradoxe des invasions provient donc de la capacité des populations invasives à se maintenir malgré une faible diversité génétique a priori [START_REF] Sax | The paradox of invasion[END_REF]Dlugosch & Parker, 2008). Il est admis que de multiples événements d'introductions, ainsi que des mécanismes épigénétiques héritables associés à l'apparition rapide de mutations suite à l'introduction d'individus dans un nouvel environnement, permettent en fait aux populations invasives de présenter rapidement une importante variabilité génétique [START_REF] Richards | Invasion of diverse habitats by few Japanese knotweed genotypes is correlated with epigenetic differentiation[END_REF][START_REF] Zhang | Epigenetics of colonizing species? A study of Japanese knotweed in Central Europe. Invasion genetics: the Baker and Stebbins legacyenetics[END_REF] [START_REF] Hutchison | Correlation of pairwise genetic and geographic distance measures: inferring the relative influences of gene flow and drift on the distribution of genetic variability[END_REF]Bélouard et al., 2019).

Il existe souvent un temps de latence important (quelques dizaines d'années à quelques centaines d'années) entre l'introduction d'une espèce non native et les impacts écologiques qu'elle engendre [START_REF] Pyšek | Invasion dynamics of Impatiens glandulifera -A century of spreading reconstructed[END_REF]. Ceci peut notamment s'expliquer par le temps inhérent à la croissance des populations et par le temps nécessaire à l'adaptation des organismes aux nouvelles contraintes environnementales. En conséquence, les études sur les processus d'invasion biologique en milieu naturel portent en général sur des invasions datant d'une soixantaine d'années et plus [START_REF] Hendry | Rapid evolution of reproductive isolation in the wild: evidence from introduced salmon[END_REF][START_REF] Lankau | Interpopulation variation in allelopathic traits informs restoration of invaded landscapes[END_REF]. Afin de mieux comprendre les mécanismes éco-évolutifs impliqués dans les invasions biologiques, il est essentiel d'étudier les populations invasives et leur variabilité intraspécifique le plus tôt possible au cours du processus d'invasion. Si les analyses génétiques sont utilisées de manière répandue pour identifier les routes d'invasion à l'échelle mondiale [START_REF] Cristescu | Genetic reconstructions of invasion history[END_REF][START_REF] Sherpa | Unravelling the invasion history of the Asian tiger mosquito in Europe[END_REF], peu d'études ont cherché à comprendre les routes d'invasion à une échelle plus locale.

Conséquences fonctionnelles de la variabilité intraspécifique des espèces invasives

Les espèces invasives peuvent induire des impacts écologiques à tous les niveaux d'organisation biologique [START_REF] Cucherousset | Ecological impacts of non-native freshwater fishes[END_REF]. Leurs impacts peuvent être directs ou indirects à travers de nombreuses interactions biotiques avec les espèces natives telles que la compétition, la prédation (Phillips & Shine, 2006;[START_REF] Walsh | Invasive species triggers a massive loss of ecosystem services through a trophic cascade[END_REF], la transmission de pathogènes [START_REF] Tompkins | Ecological replacement of native red squirrels by invasive greys driven by disease[END_REF], l'hybridation avec des espèces natives [START_REF] Mcginnity | Fitness reduction and potential extinction of wild populations of Atlantic salmon, Salmo salar, as a result of interactions with escaped farm salmon[END_REF], ou encore abiotiques, comme la modification de l'habitat [START_REF] Anderson | Ecosystem engineering by invasive exotic beavers reduces in-stream diversity and enhances ecosystem function in Cape Horn, Chile[END_REF]. Généralement les invasions biologiques résultent en des écosystèmes perturbés dans leur fonctionnement, et des structures de communauté changées [START_REF] Simberloff | Impacts of biological invasions: what's what and the way forward[END_REF].

Certaines études récentes ont montré que les effets des individus invasifs pouvaient varier entre populations [START_REF] Yonekura | Difference in the predation impact enhanced by morphological divergence between introduced fish populations[END_REF]Evangelista et al., 2019) [START_REF] Coltman | Molecular ecological approaches to studying the evolutionary impact of selective harvesting in wildlife[END_REF][START_REF] Mimura | Understanding and monitoring the consequences of human impacts on intraspecific variation[END_REF][START_REF] Závorka | Importance of harvest-driven trait changes for invasive species management[END_REF][START_REF] Závorka | Phenotypic responses of invasive species to removals affect ecosystem functioning[END_REF]Box 2).

Box 2

Importance des changements de traits induits par la gestion des espèces invasives [START_REF] Závorka | Phenotypic responses of invasive species to removals affect ecosystem functioning[END_REF]. D'autant plus que les organismes invasifs soumis à des méthodes de contrôle sont ciblés en raison de leurs forts impacts écologiques négatifs (Kopf et al., 2017), ce qui implique que le prélèvement d'individus pourrait se traduire par de fortes réponses écosystémiques.

Les coûts des programmes de lutte et de contrôle des espèces invasives étant élevés (Myers et al., 2000), les efforts mis en place sont souvent intenses, mais sur des périodes de temps relativement courtes. Par conséquent, de nombreux programmes d'éradication ne parviennent pas à réduire ou à éradiquer de manière durable les populations cibles (Britton et al., 2011). Les individus survivants permettent alors à la population de se rétablir, voire même à coloniser de nouveaux habitats à partir d'un groupe d'individus présentant des caractères phénotypiques fortement biaisés par la pression d'éradication.

Le contrôle des espèces invasives reste un outil de gestion essentiel qui permet parfois l'élimination complète de populations invasives (Britton et al., 2011;Kopf et al., 2017).

Cependant [START_REF] Mcdonald | Report of the United States Commissioner of Fish and Fisheries for the fiscal years 1889-1890 and 1890-1891[END_REF][START_REF] Petrusek | Distribution of the invasive spiny-cheek crayfish (Orconectes limosus) in the Czech Republic. Past and present[END_REF].

De [START_REF] Holdich | The spiny-cheek crayfish, Orconectes limosus (Rafinesque, 1817) [Crustacea: Decapoda: Cambaridae], digs into the UK[END_REF]. L'espèce possède un cycle de vie rapide et une forte fécondité avec deux périodes de reproduction sur l'année permettant aux populations de croître rapidement, ce qui peut en partie expliquer son succès invasif [START_REF] Kozák | The fecundity, time of egg development and juvenile production in spiny-cheek crayfish (Orconectes limosus) under controlled conditions[END_REF][START_REF] Chybowski | Morphometrics, fecundity, density, and feeding intensity of the spinycheek crayfish, Orconectes limosus (Raf.) in natural conditions[END_REF]. F. limosus est également capable de se reproduire par parthénogénèse, ce qui pourrait lui conférer un avantage non négligeable sur les autres espèces s'il s'avérait qu'elle utilise ce mode de reproduction en milieu naturel [START_REF] Buřič | A successful crayfish invader is capable of facultative parthenogenesis: a novel reproductive mode in decapod crustaceans[END_REF][START_REF] Buřič | Reproductive plasticity in freshwater invader: from long-term sperm storage to parthenogenesis[END_REF]. Son régime alimentaire omnivore est principalement composé de végétaux et de détritus [START_REF] Vojkovská | The diet of the spiny-cheek crayfish Orconectes limosus in the Czech Republic[END_REF]. L'écrevisse américaine possède une grande capacité de dispersion aquatique par les réseaux hydrographiques, mais une occurrence de dispersion terrestre pour cette espèce a déjà été reportée [START_REF] Puky | Invasive crayfish on land: Orconectes limosus (rafinesque, 1817) (decapoda: Cambaridae) crossed a terrestrial barrier to move from a side arm into the danube river at Szeremle, Hungary[END_REF].

L'écrevisse de Louisiane, Procambarus clarkii

L'écrevisse de Louisiane (red swamp crayfish en anglais) est originaire du sud des États-Unis et du nord-ouest du Mexique [START_REF] Gherardi | Crayfish invading Europe: the case study of Procambarus clarkii[END_REF] [START_REF] Souty-Grosset | Atlas of crayfish in Europe. Patrimoines naturels 64[END_REF][START_REF] Oficialdegui | Brought more than twice: the complex introduction history of the red swamp crayfish into Europe[END_REF].

Tout comme F. limosus, P. clarkii possède une croissance rapide, une grande fécondité et une à deux périodes de reproduction par an [START_REF] Gherardi | Crayfish invading Europe: the case study of Procambarus clarkii[END_REF][START_REF] Alcorlo | Reproductive biology and life cycle of the invasive crayfish Procambarus clarkii (Crustacea: Decapoda) in diverse aquatic habitats of South-Western Spain: implications for population control[END_REF]. Elle se caractérise également par une grande tolérance thermique ainsi qu'à la dessiccation, et peut également occuper une grande diversité d'habitats dulçaquicoles et salins [START_REF] Gherardi | Crayfish invading Europe: the case study of Procambarus clarkii[END_REF].

P. clarkii est une espèce omnivore opportuniste qui consomme principalement des végétaux et détritus au stade adulte, mais peut également se nourrir de larves d'insectes ou d'oeufs de poissons [START_REF] Correia | Food choice by the introduced crayfish Procambarus clarkii[END_REF][START_REF] Alcorlo | Feeding preferences and food selection of the red swamp crayfish, Procambarus clarkii, in habitats differing in food item diversity[END_REF]. L'écrevisse de Louisiane possède non seulement une grande capacité de dispersion par voie aquatique, mais elle peut également se déplacer par voie terrestre (Gherardi & Barbaresi, 2000;[START_REF] Thomas | Terrestrial emigration behaviour of two invasive crayfish species[END_REF]. de nombreux impacts dans les écosystèmes colonisés [START_REF] Twardochleb | A global meta-analysis of the ecological impacts of nonnative crayfish[END_REF]. Elles érodent les berges des cours d'eau ou des lacs en creusant des terriers, et ont par la même occasion une activité de bioturbation qui modifie la biodisponibilité des nutriments pour les autres organismes de l'écosystème et qui peut impacter à son tour la production de macrophytes [START_REF] Statzner | Crayfish as geomorphic agents and ecosystem engineers: biological behavior affects sand and gravel erosion in experimental streams[END_REF][START_REF] Gherardi | Understanding the impact of invasive crayfish[END_REF][START_REF] Holdich | The spiny-cheek crayfish, Orconectes limosus (Rafinesque, 1817) [Crustacea: Decapoda: Cambaridae], digs into the UK[END_REF][START_REF] Souty-Grosset | The red swamp crayfish Procambarus clarkii in Europe: impacts on aquatic ecosystems and human well-being[END_REF]. Globalement, elles provoquent un déclin de biodiversité dans les écosystèmes natifs (e.g. macrophytes, macroinvertébrés, oeufs et larves de poissons et d'amphibiens ; [START_REF] Souty-Grosset | The red swamp crayfish Procambarus clarkii in Europe: impacts on aquatic ecosystems and human well-being[END_REF], et par leur régime omnivore généraliste elles peuvent impacter les chaînes trophiques à de multiples niveaux et modifier les dynamiques des communautés [START_REF] Renai | Predatory efficiency of crayfish: comparison between indigenous and non-indigenous species[END_REF]. Par leur forte voracité, les écrevisses invasives peuvent affecter la décomposition de la litière, un processus écosystémique fondamental qui intervient notamment dans le recyclage du carbone [START_REF] Duffy | Biodiversity and ecosystem function: the consumer connection[END_REF][START_REF] Dunoyer | Effects of crayfish on leaf litter breakdown and shredder prey: are native and introduced species functionally redundant?[END_REF][START_REF] Carvalho | Direct and indirect effects of an invasive omnivore cray fish on leaf litter decomposition[END_REF]. Ces deux espèces ont également une agressivité plus importante que la plupart des écrevisses natives, ce qui leur confère un avantage lors d'interactions de compétition interspécifique [START_REF] Gherardi | Agonism and interference competition in freshwater decapods[END_REF]. Leurs caractéristiques morphologiques (taille de corps et des pinces) sont aussi déterminantes dans les interactions de compétition et de défense vis-à-vis de potentiels prédateurs [START_REF] Butler | An analysis of the mechanisms governing species replacements in crayfish[END_REF][START_REF] Garvey | Scaledependent associations among fish predation, littoral habitat, and distributions of crayfish species[END_REF][START_REF] Pintor | Differences in aggression, activity and boldness between native and introduced populations of an invasive crayfish[END_REF][START_REF] Graham | Claw size predicts dominance within and between invasive species of crayfish[END_REF]. Enfin, F. limosus et P. clarkii sont toutes deux porteuses saines du champignon responsable de la peste des écrevisses, Aphanomyces astaci, et constituent donc une menace pour les populations d'écrevisses indigènes [START_REF] Holdich | A review of the ever increasing threat to European crayfish from non-indigenous crayfish species[END_REF].

Sites d'étude

Ce travail de thèse a été réalisé dans le sud-ouest de la France, dans des lacs artificiels situés dans la plaine alluviale de la Garonne, au sud de Toulouse. However, genetic assessments aimed at identifying invasion pathways at local scales remain scarce, despite their importance for guiding biological invasions management.

2-We used genetic analyses to identify local invasion pathways used by two invasive crayfish species (Faxonius limosus and Procambarus clarkii) to invade a dense network of artificial lakes displaying high spatio-temporal dynamics and hosting multiple socio-economic activities. We first characterized spatial patterns of genetic variation for each species using neutral microsatellite markers. We then identified their environmental determinants, and inferred the potential local invasion pathways they might have used for invading the study area.

3-We revealed contrasting patterns of genetic variability for both species: F. limosus displayed very low levels of genetic diversity and spatial structuring, while P. clarkii displayed much higher genetic diversities and spatial genetic structuring levels. We also highlighted context-dependent effects of different environmental variables, with notably a promoting effect of fishery management practices on both species' genetic diversities. 4-We found little evidence for the deliberate release and contaminant pathways for F. limosus, probably because its low levels of genetic variability precluded a clear identification of its local invasion pathways. We found however clear evidence of the co-occurrence of multiple invasion pathways (release, contaminant, unaided/corridor spread and stowaway) at the local scale for P. clarkii.

5-Synthesis and applications:

We illustrate both the usefulness and limitations of neutral genetic variation assessments for inferring local invasion pathways in complex environments. This approach is particularly useful for species with complex invasion histories that display sufficient levels of genetic diversity, but may fail identifying all local invasion pathways in IAS displaying very low levels of genetic variability.

Introduction

Rates of introduction, establishment and subsequent range expansion of Invasive Alien Species (hereafter, IAS) are increasing, promoting a global rise in the number of biological invasions [START_REF] Seebens | No saturation in the accumulation of alien species worldwide[END_REF][START_REF] Seebens | Global rise in emerging alien species results from increased accessibility of new source pools[END_REF]. Invasive species exert negative economic and ecological effects [START_REF] Simberloff | Impacts of biological invasions: what's what and the way forward[END_REF][START_REF] Jeschke | Defining the impact of non-native species[END_REF] and act across levels of biological organization, ranging from changes in the genetic composition of native species (e.g. hybridization) to species extirpation and changes in ecosystem functioning [START_REF] Cucherousset | Ecological impacts of non-native freshwater fishes[END_REF][START_REF] Simberloff | Impacts of biological invasions: what's what and the way forward[END_REF][START_REF] Jeschke | Defining the impact of non-native species[END_REF]. Improving our ability to characterize and predict biological invasions is thus urgently needed for engaging efficient IAS management.

Invasion genetics allow reconstructing complex invasion histories through the inferential and correlative analysis of the genetic footprints left by different processes during invasions [START_REF] Barrett | Foundations of invasion genetics: the Baker and Stebbins legacy[END_REF][START_REF] Cristescu | Genetic reconstructions of invasion history[END_REF]. Indeed, founder effects (Dlugosch & Parker, 2008b), population size changes [START_REF] Beaumont | Detecting population expansion and decline using microsatellites[END_REF], admixture [START_REF] Dlugosch | The devil is in the details: genetic variation in introduced populations and its contributions to invasion[END_REF], or interspecific hybridization (e.g. [START_REF] Bay | Parallel introgression and selection on introduced alleles in a native species[END_REF] shape intraspecific genetic characteristics of invasive populations. Genetic analyses reveal patterns of variation across invasive populations, facilitating hypotheses-driven reconstruction of invasion histories (e.g. [START_REF] Rey | Elucidating the spatio-temporal dynamics of an emerging wildlife pathogen using approximate Bayesian computation[END_REF] and informing global invasion pathways at large -national, continental or worldwide-spatial scales [START_REF] Oficialdegui | Unravelling the global invasion routes of a worldwide invader, the red swamp crayfish (Procambarus clarkii)[END_REF][START_REF] Sherpa | Unravelling the invasion history of the Asian tiger mosquito in Europe[END_REF]). Yet, genetic assessments identifying local invasion pathways are scarce despite their importance for the management of biological invasions.

The identification of invasion pathways and spread vectors is crucial for (i) containing ongoing invasions by reducing propagule pressure [START_REF] Simberloff | The role of propagule pressure in biological invasions[END_REF][START_REF] Pergl | Troubling travellers: are ecologically harmful alien species associated with particular introduction pathways?[END_REF], (ii) preventing invasive populations to act as bridgehead populations [START_REF] Lombaert | Bridgehead effect in the worldwide invasion of the biocontrol Harlequin ladybird[END_REF][START_REF] Bertelsmeier | Bridgehead effects and role of adaptive evolution in invasive populations[END_REF], and (iii) hindering recolonization after successful eradication (Britton et al., 2011).

Six major introduction pathways have been identified [START_REF] Hulme | Grasping at the routes of biological invasions: a framework for integrating pathways into policy[END_REF] : deliberate release as a commodity, escape from captivity, contaminant of a specific commodity, stowaway on a transport vector, and spread through unaided dispersal from an invaded area, or through dispersal following anthropogenic corridors [START_REF] Hulme | Grasping at the routes of biological invasions: a framework for integrating pathways into policy[END_REF][START_REF] Essl | Crossing frontiers in tackling pathways of biological invasions[END_REF][START_REF] Hulme | Invasion pathways at a crossroad: policy and research challenges for managing alien species introductions[END_REF]. When an invasion history is relatively simple (e.g. few introductions from identified sources; [START_REF] Simon | Invasive cyprinid fish in Europe originate from the single introduction of an admixed source population followed by a complex pattern of spread[END_REF], pathway identification is usually robust. However, biological invasions are often the result of complex socio-ecological interactions involving multiple and often unreported introductions, propagules per introduction event and source populations [START_REF] Blackburn | The influence of numbers on invasion success[END_REF][START_REF] Rey | Elucidating the spatio-temporal dynamics of an emerging wildlife pathogen using approximate Bayesian computation[END_REF]. The information contained in the genetic footprints of a given pathway depend on multiple intrinsic factors such as species traits (e.g. dispersal capacities, demography, invasion history) and extrinsic factors such as distances between populations, physical configuration of ecosystems, or the socio-economic activities occurring in the study area [START_REF] Washburn | Small fish, large river: surprisingly minimal genetic structure in a dispersal-limited, habitat specialist fish[END_REF]. Consequently, the knowledge gained from population genetics analyses can be highly variable and may modulate our ability to identify local invasion pathways.

Here, we aim to identify local invasion pathways of two global invasive crayfish (spiny cheek crayfish Faxonius limosus and red swamp crayfish Procambarus clarkii) exhibiting contrasting ecology and invasion histories in Europe [START_REF] Filipová | Haplotype variation in the spinycheek crayfish Orconectes limosus: colonization of Europe and genetic diversity of native stocks[END_REF][START_REF] Oficialdegui | Unravelling the global invasion routes of a worldwide invader, the red swamp crayfish (Procambarus clarkii)[END_REF] using genetic analyses. We used as model ecosystems a dense network of artificial gravel pit lakes displaying high spatio-temporal dynamics and hosting a myriad of socio-economic activities within a restricted spatial scale (Evangelista et al., 2015;[START_REF] Zhao | Environmental determinants of fish community structure in gravel pit lakes[END_REF]. We first quantified the spatial distribution of genetic variation for each species using neutral microsatellite markers. We then identified the potential environmental determinants of genetic variation patterns. We finally interpreted our empirical results in the light of Hulme's et al. invasion pathways classification to (i) identify potential local invasion pathways having been used by the two IAS for invading the study area and to (ii) discuss the assets and limitations of our approach with respect to the contrasting patterns of genetic variation we observed for the two species.

Material & methods

Model organisms

Our model organisms were two invasive crayfish species (listed in the European Union Regulation EU 1143/2014 and EU 2019/1262) displaying contrasting life-history traits and invasion histories at the European scale. Faxonius limosus is native from the Eastern Coast of North America [START_REF] Filipová | Haplotype variation in the spinycheek crayfish Orconectes limosus: colonization of Europe and genetic diversity of native stocks[END_REF]. Its only known successful introduction in Europe is from 1890 when 90 individuals from the US Commission of Fish and Fisheries were introduced in western Poland [START_REF] Filipová | Haplotype variation in the spinycheek crayfish Orconectes limosus: colonization of Europe and genetic diversity of native stocks[END_REF]. The species subsequently spread across Europe andarrived in central France between 1911 and1913, where 2,000 individuals from Germany were deliberately released [START_REF] Buffault | Une écrevisse américaine acclimatée en France: le Cambarus du Cher[END_REF][START_REF] Laurent | Introductions d'écrevisses en France et dans le monde, historique et conséquences[END_REF]. It invaded the Garonne river basin in the early 1960s [START_REF] Laurent | Les écrevisses en France[END_REF][START_REF] Laurent | Introductions d'écrevisses en France et dans le monde, historique et conséquences[END_REF] and its presence in the study area was first documented in 1988 [START_REF] Magnier | L'enquête nationale sur les écrevisses[END_REF]. Procambarus clarkii is native from Southern U.S.A. and North-eastern Mexico and has been widely introduced worldwide, colonizing almost all continents [START_REF] Oficialdegui | Unravelling the global invasion routes of a worldwide invader, the red swamp crayfish (Procambarus clarkii)[END_REF]. It has been first introduced in Europe in 1973 from Louisiana to Spain, but the species rapidly spread across Europe [START_REF] Oficialdegui | Unravelling the global invasion routes of a worldwide invader, the red swamp crayfish (Procambarus clarkii)[END_REF]. In France, the first introduction is reported in South-western France in 1976 with individuals from Spain [START_REF] Laurent | Introductions d'écrevisses en France et dans le monde, historique et conséquences[END_REF]. Besides this introduction event, many individuals were imported from Spain and Kenya for aquaculture from the late 1970s to the early 1980s [START_REF] Holdich | A review of astaciculture: freshwater crayfish farming[END_REF][START_REF] Oficialdegui | Unravelling the global invasion routes of a worldwide invader, the red swamp crayfish (Procambarus clarkii)[END_REF][START_REF] Oficialdegui | Brought more than twice: the complex introduction history of the red swamp crayfish into Europe[END_REF]. The presence of P. clarkii in our study area was first mentioned in 1995 [START_REF] Changeux | Évolution de la répartition des écrevisses en France Métropolitaine selon les enquêtes nationales mensées par le conseil supérieur de la pêche de 1977 à 2001[END_REF].

Study area and sampling design

The study area was composed of a network of artificial gravel pit lakes, isolated and disconnected from the hydrographic network, of different ages (from 10 to 60 years) located within a 70 x 75 km area located within the Garonne floodplain (South-western France; III.S1-2), representing a set of isolated aquatic islands within a terrestrial landscape matrix [START_REF] Hortal | Perspectives on the use of lakes and ponds as model systems for macroecological research[END_REF][START_REF] Zhao | Environmental determinants of fish community structure in gravel pit lakes[END_REF]. They are also distributed along a decreasing North-to-South urbanisation gradient (i.e. Toulouse metropolitan area on the North, and Pyrenees Mountains' piedmont on the South) and host multiple socio-economic and recreational activities including angling, leisure and water sports [START_REF] Santoul | Importance of gravel pits for the conservation of waterbirds in the Garonne river floodplain (southwest France)[END_REF]Evangelista et al., 2015). Their fishery management in term of angling practices and fish stocking can be categorized as high level when managed by public and private angling clubs, and as low level when managed by municipalities or private owners [START_REF] Zhao | Environmental determinants of fish community structure in gravel pit lakes[END_REF]. This area is particularly interesting for studying local invasion pathways because many major pathways identified by [START_REF] Hulme | Grasping at the routes of biological invasions: a framework for integrating pathways into policy[END_REF] can potentially (co-)occur here for F. limosus and P. clarkii: deliberate releases in specific lakes for human consumption, contaminants of commodities (e.g. during fish stocking events), stowaways on transport vectors (e.g.

dispersed from one lake to another by humans or aquatic birds; [START_REF] Anastácio | Waterbirdmediated passive dispersal is a viable process for crayfish (Procambarus clarkii)[END_REF][START_REF] Coughlan | Up, up and away: birdmediated ectozoochorous dispersal between aquatic environments[END_REF], and unaided/corridor spread, by dispersing overland, through roads, or through the riverine network [START_REF] Puky | Invasive crayfish on land: Orconectes limosus (rafinesque, 1817) (decapoda: Cambaridae) crossed a terrestrial barrier to move from a side arm into the danube river at Szeremle, Hungary[END_REF][START_REF] Thomas | Terrestrial emigration behaviour of two invasive crayfish species[END_REF].

The sampling was conducted from mid-September to mid-October 2016-2019 primarily using pairs of baited traps (a cylindrical trap of 62 x 34 x 34 cm, with a mesh size of 10 mm, and a rectangular trap of 95 x 20 x 20 cm with a mesh size of 4 mm) set both overnight (n = 12 traps) and during the day (n = 8; [START_REF] Alp | Phenological response of a key ecosystem function to biological invasion[END_REF][START_REF] Závorka | Phenotypic responses of invasive species to removals affect ecosystem functioning[END_REF]. We also performed active sampling using dip nets when needed. Additional samples were provided by local anglers and angling agencies. We successfully sampled 18 populations of F. limosus (514 genotyped individuals) and 43 populations of P. clarkii (1,182 genotyped individuals; Figure III.1). We targeted at least N = 28 sampled individuals per population per species for subsequent genetic analyses, although this number was not always reached (77.78% of F. limosus populations with N ≥ 20, mean N across populations = 29, SD = 13, Table III.S1 and 83.72% of P. clarkii populations with N ≥ 20, mean N across populations = 27, SD = 7, Table III.S2).

• • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • BOC INN

Environmental variables

A set of environmental variables was collected to perform subsequent landscape genetics analyses. Lake surface area (km²) was calculated using aerial pictures (IGN 2019). We further determined both Euclidean and shortest topological (i.e. riverine) distances between (i) each pair of lakes and (ii) between each lake and Toulouse city using the R package 'riverdist' [START_REF] Tyers | riverdist: river network distance computation and applications[END_REF]. Distances between lakes and Toulouse can be viewed as a proxy of an urbanisation gradient, with decreasing urbanisation pressure with increasing distance. Given that both Euclidean and topological distances were highly correlated (Pearson's correlation coefficient r between both distances = 0.997 and 0.993 for F. limosus and P. clarkii respectively), we only used Euclidean distances for subsequent analyses. Finally, we quantified the level of fishery management as previously described (high/low level management).

Genotyping

Genomic DNA was extracted from abdominal muscle tissue using a modified salt-extraction protocol [START_REF] Aljanabi | Universal and rapid salt-extraction of high quality genomic DNA for PCR-based techniques[END_REF]. We co-amplified 9 and 14 microsatellite loci for F. limosus and P. clarkii, respectively [START_REF] Hulák | Cross-species amplification of microsatellite markers in the invasive spiny-cheek crayfish (Orconectes limosus): assessment and application[END_REF][START_REF] Jiang | Microsatellite marker identification from transcriptome derived sequences of the red swamp crawfish, Procambarus clarkii[END_REF], using two (F. limosus)

or three (P. clarkii) multiplexed PCRs, 5-20 ng of genomic DNA and QIAGEN® Multiplex PCR Kits (Qiagen, Valencia, CA, USA). Details on loci, primer concentrations, PCR conditions and multiplex sets are available elsewhere [START_REF] Hulák | Cross-species amplification of microsatellite markers in the invasive spiny-cheek crayfish (Orconectes limosus): assessment and application[END_REF][START_REF] Jiang | Microsatellite marker identification from transcriptome derived sequences of the red swamp crawfish, Procambarus clarkii[END_REF][START_REF] Lang | Stable resource polymorphism along the benthic littoral-pelagic axis in an invasive crayfish[END_REF].

Genotyping was conducted on an ABI PRISM™ 3730 Automated Capillary Sequencer (Applied Biosystems, Foster City, CA, USA), and allele size scoring using GENEMAPPER® v.4.0 (Applied Biosystems, Waltham, USA).

Genotyping quality controls

For each species, we assessed (i) null alleles and potential scoring errors incidence with MICROCHECKER 2.3 [START_REF] Van Oosterhout | MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data[END_REF], (ii) linkage disequilibria among loci within populations with FSTAT v2.9.3.2 [START_REF] Goudet | FSTAT (Version 1.2): a computer program to calculate F-statistics[END_REF] and (iii) departures from Hardy-Weinberg (HW) equilibrium with GENEPOP v4.0 [START_REF] Rousset | GENEPOP'007: a complete re-implementation of the GENEPOP software for Windows and Linux[END_REF]. Levels of significance for these multiple tests were adjusted using the false discovery rate (FDR) procedure of [START_REF] Benjamini | Controlling the false discovery rate: a practical and powerful approach to multiple testing[END_REF]. Finally, we used BAYESCAN v.2.1 [START_REF] Foll | A genome-scan method to identify selected loci appropriate for both dominant and codominant markers: a Bayesian perspective[END_REF] to test the neutrality of the microsatellite datasets. We specifically ran four MCMC chains considering 100 prior odds for neutral model, sample sizes of 10,000 (with thinning intervals of 50), burnin periods of 50,000 and 20 pilot runs with lengths of 5,000 per chain. The convergence of the four chains per species was checked through a Gelman and Rubin analysis [START_REF] Gelman | Inference from iterative simulation using multiple sequences[END_REF]) using a modified script from [START_REF] Paz-Vinas | The demographic history of populations experiencing asymmetric gene flow: combining simulated and empirical data[END_REF]. We considered that chains reached convergence when values lower than 1.1 were obtained [START_REF] Gelman | Data analysis using regression and multilevel/hierarchical models[END_REF].

Genetic diversity and structure

We assessed for each species and populations their genetic diversity levels by calculating (over all loci and for each population and species) both allelic richness (AR) and private allelic richness (PA) indices using the rarefaction procedures implemented in ADZE v.1.0 [START_REF] Szpiech | ADZE: a rarefaction approach for counting alleles private to combinations of populations[END_REF]. We assumed minimum sample sizes for rarefaction of N = 11 and N = 12 for F. limosus and P. clarkii respectively (i.e. minimum sample size for both species; Tables III.S1-2). We also estimated (across loci for each species and populations) expected heterozygosities (Hexp) using GENETIX v.4.05 [START_REF] Belkhir | GENETIX 4.05, logiciel sous Windows TM pour la génétique des populations[END_REF] and the Garza & Williamson ( 2001) statistic (GW) using the R package 'strataG' [START_REF] Archer | stratag: an r package for manipulating, summarizing and analysing population genetic data[END_REF]. Values of GW lower than 0.68 are indicative of recent genetic bottlenecks (i.e. due to a recent population collapse or a founder event following an introduction; [START_REF] Garza | Detection of reduction in population size using data from microsatellite loci[END_REF]. Finally, we calculated, for each species, pairwise genetic differentiation values (i.e. Fst) with the program FSTAT v2.9.3.2 [START_REF] Goudet | FSTAT (Version 1.2): a computer program to calculate F-statistics[END_REF]. We then calculated for each population and species the average of all pairwise Fst values estimated between one given population and all the remaining to obtain a within-population genetic uniqueness value (i.e. FstUNI; [START_REF] Paz-Vinas | Systematic conservation planning for intraspecific genetic diversity[END_REF].

Spatial distribution of genetic diversity and spatial patterns of genetic differentiation

We first mapped AR, PA, and FstUNI to visually assess the spatial structure of genetic diversity and uniqueness. As Hexp were highly correlated with AR (Pearson's r=0.958 and 0.950 for F. limosus and P. clarkii respectively), they were not mapped. We then tested whether Isolation-By-Distance (IBD) patterns exist by exploring the relationship between pairwise Euclidean distances and pairwise Fst values by conducting single Mantel tests with 1,000 permutations with the R package 'vegan' [START_REF] Oksanen | vegan: community ecology package[END_REF]. We finally used the R package 'segmented' [START_REF] Muggeo | segmented: an R package to fit regression models with broken-line relationships[END_REF] to identify breakpoints on the IBD relationship using piecewise regressions based on generalized linear models [START_REF] Prunier | Contribution of spatial heterogeneity in effective population sizes to the variance in pairwise measures of genetic differentiation[END_REF]. These breakpoints indicate significant changes in the relative strength of genetic drift vs. gene flow on pairwise genetic differentiation.

Genetic clustering analyses

Genetically homogenous groups of individuals (i.e. clusters) were identified using the R package 'rmavericK' [START_REF] Verity | Estimating the number of subpopulations (K) in structured populations[END_REF] which uses thermodynamic integration (TI)

procedures to estimate the best K number of clusters [START_REF] Verity | Estimating the number of subpopulations (K) in structured populations[END_REF]. We explored values of K ranging from 1 to 18 for F. limosus and from 1 to 20 for P. clarkii, considering two different evolutionary models (i.e. with and without admixture). We ran MCMC chains considering burn-in periods of 10,000 iterations, 2,000 sampling iterations, and rung parameter equal to 10. We then determined for each species and evolutionary model (i.e.

with/without admixture) the best K value according to the obtained TI posterior probabilities.

Finally, we compared the evidences of the two tested evolutionary models to determine which one better fits our genotypic data.

Environmental determinants of genetic diversity and structure

To identify the environmental determinants of genetic variability, we build linear models using AR, PA and FstUNI as dependent variables, and surface, distance and management as explanatory variables. All full models were run with two-way interactions and the best models were selected using a backward-selection procedure using R v.2.6.2. Marginal effects of significant interactions were plotted using the R package 'sjPlot' [START_REF] Lüdecke | sjPlot: data visualization for statistics in social science[END_REF].

Results

Genotyping quality controls

We removed one locus (PCSH0042) for F. limosus that was monomorphic for all populations, and two loci for P. clarkii (PCLG27: presence of null alleles; PCSH0089: signals of purifying or balancing selection; see details in Appendix III.1).

Genetic diversity and structure

Spatial patterns of genetic diversity and structure

No significant IBD pattern was observed for F. limosus p=0.905,Figure III.3a), but there was a significant IBD pattern for P. clarkii (Mantel r=0.371,p<0.001,Figure III.3b). Piecewise regressions revealed breakpoints of the positive relationship between genetic differentiation and distance at the very short distance of 1.166 km (CI95% = [0.887-

• • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • N 0 7.5 15 km (b) • • • • • • ≤ 1.280 ≤ 1.410 ≤ 1.540 ≤ 1.660 ≤ 1.790 ≤ 1.920 • • • • • • ≤ 0.113 ≤ 0.137 ≤ 0.162 ≤ 0.186 ≤ 0.210 ≤ 0.235
Faxonius limosus

• • • • • • • • • • • • • • • • • • • • • • • • • • ≤ 0.056 ≤ 0.112 ≤ 0.167 ≤ 0.222 ≤ 0.278 ≤ 0.333 • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • ≤ 2.820 ≤ 3.230 ≤ 3.640 ≤ 4.050 ≤ 4.460 ≤ 4.875 • • • • • • ≤ 0.038 ≤ 0.075 ≤ 0.112 ≤ 0.149 ≤ 0.186 ≤ 0.224 • • • • • • ≤ 0.153 ≤ 0.186 ≤ 0.218 ≤ 0.251 ≤ 0.284 ≤ 0.317 Procambarus clarkii Allelic Richness (AR) Private Allelic richness (PA) Genetic uniqueness (Fst UNI ) (a) (d) (c) (f) (e)

Genetic clustering

For F. limosus, the two evolutionary models were similarly supported ( and some populations belonging principally to a specific cluster displaying introgression from individuals belonging to a different cluster (e.g. introgression of cluster 4, mainly represented

0.0 0.1 0.2 0.3 0.4 0.5 • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • •• • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • •• • • • • • • • • • • • • • •• • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • •• • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • •• • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • •• • • • • • • • • • • • • • • • • • • • • • • • • • • •• • • • • • • • • • • • • 0.0 0.1 0.2 0.3 0.4 • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • Euclidean distance between lakes (in km)

Factors explaining observed patterns of genetic diversity and structure

We found a significant interaction term (Distance x Surface: F1,13=8.0014, p=0.014) for AR of F. limosus (Table III

Discussion

The present study revealed very contrasting patterns of genetic variability for two invasive alien crayfish species co-occurring in a dense network of artificial lakes. One species (Faxonius limosus) displayed very low levels of genetic diversity and unclear spatial patterns of genetic structure, preventing a clear identification of its potential local invasion pathways.

Contrastingly, the second crayfish species (Procambarus clarkii) displayed higher genetic diversity and spatial genetic structuring, allowing identifying specific genetic footprints that suggest that the invasion of the network of artificial lakes by this species has been fuelled by the co-occurrence of multiple local invasion pathways. Our analyses also indicate a contextdependent effect of fishery management practices on genetic diversity that may promote genetic diversity due to deliberate (release pathway) or undeliberate introductions as contaminants (during fish stocking events) of genetically-distinct individuals. Overall, our results illustrate both the usefulness and limitations of neutral genetic variation assessments for inferring local invasion pathways in complex environments.

Low levels of genetic variability in F. limosus preclude the identification of local invasion pathways

The Faxonius limosus meta-population was composed of populations characterized by very low genetic diversities. The GW statistic revealed evidence of genetic bottlenecks in all populations, suggesting that the observed low levels of genetic diversity are probably due to founder effects having occurred during the species spread and the local colonisation of lakes.

Additionally, facultative parthenogenesis has been reported under controlled conditions in females of this species [START_REF] Buřič | A successful crayfish invader is capable of facultative parthenogenesis: a novel reproductive mode in decapod crustaceans[END_REF][START_REF] Buřič | Reproductive plasticity in freshwater invader: from long-term sperm storage to parthenogenesis[END_REF]. Although this life-history trait may partly explain the observed low levels of genetic variability, its occurrence in natural conditions (and in the studied ecosystems specifically) remains unknown. Our analyses of genetic variability (using AR, PA and FstUNI) only provided moderate evidence of local invasion pathways. For instance, very high PA and high AR values found for the south-western-most population (SED; Figure III.2a-2c) suggest that it may originate from an independent introduction event, probably due to a deliberate release or as a contaminant of a fish stocking.

We failed to detect a significant IBD pattern for this species, which prevented us to identify whether unaided/corridor spread pathways may have occurred. Pairwise Fst values were highly idiosyncratic, with pairs of populations separated by comparable distances displaying highly variable genetic differentiation. Although this idiosyncrasy may suggest the cooccurrence of multiple invasion pathways different than the unaided/corridor spread pathways, the very low levels of genetic diversity observed for F. limosus have probably blurred our ability to infer any local invasion pathway. The presence of two genetic clusters in the study area may suggest the introduction and subsequent admixture of two geneticallydistinct groups, although this hypothesis probably does not hold true. Alternatively, the lack of clear genetic structuring may be a consequence of the very low levels of genetic diversity.

With this reduced genetic pool, the differential effects of genetic drift in populations may be driving a first subset of populations to fix a similar set of alleles by chance (e.g. cluster 1; Figure III.4a), while driving a second subset of populations to fix a second subset of alleles (e.g. cluster 2; Figure III.4a).

Finally, we found that PA increases with lake surface in lakes that are experiencing strong fishery management, suggesting that populations from larger managed lakes which likely received more stocking (quantity and frequency) are more prone to receive distinct (and unique) alleles from different sources through the contaminant pathway.

Local invasion pathways for P. clarkii

Values of AR, Hexp and FstUNI for P. clarkii were overall higher than for F. limosus, and PA values were diverse across populations. As for F. limosus, all P. clarkii populations displayed evidence of recent genetic bottlenecks. Given that the invasion of this species is relatively recent, and given the high densities of P. clarkii in almost all sampled lakes, these bottleneck footprints are probably due to recent founder events. These genetic patterns provided us with a robust playground to identify genetic footprints potentially linked to local invasion pathways.

For instance, the TAC population, which experiences low level fishery management practices, displayed the highest values for AR, PA and Hexp, suggesting that it may originate from an independent introduction, probably due to a deliberate release. The SOD population, for instance, also displayed a high PA and a moderate FstUNI, suggesting that it can be the result of an independent deliberate release event instead of a colonisation by individuals from other bridgehead populations through the unaided/corridor spread pathways.

The sharp increase of pairwise Fst values in P. clarkii at short distances suggests that (i) neighboring populations are strongly isolated from each other, (ii) populations exchange very low numbers of migrants per generation, or that (iii) differential effects of genetic drift are fuelling population differentiation in lakes. These results agree with a recent study (Bélouard et al., 2019b) and suggest that a stepwise invasion process with a colonization front progressing through lakes (through unaided/corridor spread) may have occurred, with subsequent isolation and differentiation of small lake populations due to differential genetic drift effects. We found nonetheless high variability in pairwise Fst values for couples of populations separated by similar distances, suggesting that other invasion pathways (e.g. contaminant, release, stowaway) might co-occur.

The occurrence of multiple local invasion pathways for P. clarkii was confirmed by the genetic clustering analyses. Indeed, we detected a very high number of genetic clusters (15) despite the small spatial scale (~5,000 km²). Some of these clusters were only represented by Finally, we found that management practices may promote genetic diversity of P. clarkii and reduce among-lakes genetic differentiation, notably through an increased occurrence of releases as contaminants. This may be exacerbated in larger lakes with higher carrying capacities such as for F. limosus, but also in lakes that are distant from the main city, as they might be more attractive for anglers that want getaways from urbanised areas for leisure angling.

Conclusions

Overall, the patterns of genetic variation of F. limosus are congruent with the mainstream hypothesis of Europe's invasion history by this species: a probable strong genetic bottleneck due to a strong founder event in 1890, followed by successive founder events during subsequent introductions and colonization events across Europe. Although our analyses suggest that the release and contaminant pathways may have played an important role, the very low levels of genetic variability observed for this IAS may have precluded a clear identification of all the local invasion pathways used by this IAS to invade the studied ecosystem. Contrarily, the patterns of genetic variation we observed for Procambarus clarkii suggest that this species is able to use many different pathways (mainly release and contaminant, but also stowaway and unaided/corridor spread pathways) at a local scale to invade a given area, hence confirming the co-occurrence of multiple invasion pathways observed for this species at the global scale [START_REF] Oficialdegui | Unravelling the global invasion routes of a worldwide invader, the red swamp crayfish (Procambarus clarkii)[END_REF][START_REF] Oficialdegui | Brought more than twice: the complex introduction history of the red swamp crayfish into Europe[END_REF].

We also highlight that fishery management activities may have played an important role on the dissemination of these two IAS across the network of artificial gravel pit lakes we studied, by having promoted genetic diversities in lakes experiencing high level fishery management practices, probably through deliberate releases or undeliberate releases as contaminants of genetically-distinct individuals. Although further work is still needed to better assess the effects that fisheries and angling practices may have had on the genetic diversity of these IAS (e.g. by compiling information on the number, intensity and origin of crayfish/fish releases in lakes), we argue that fish stocking must be conducted very carefully to impede the reinforcement of crayfish populations with new genetic variants in already-colonised lakes, and to avoid the colonization of new lakes or of lakes having experienced removal programs.

Here, we illustrate both the usefulness and limitations of neutral genetic variation assessments for inferring local invasion pathways in complex environments. This approach is particularly useful in species having experienced complex invasion histories such as P. clarkii, as these species will tend to display high levels of genetic diversity, providing a robust playground to identify the genetic signals of many concomitant local invasion pathways.

However, this approach may only provide limited information on local invasion pathways for IAS displaying very low levels of genetic variability due to strong genetic bottlenecks, to particularities of their reproductive mode (clonal and/or parthenogenetic reproduction modes), or a potential combination of both, such as for Faxonius limosus. Combining genetic assessments with other complementary approaches such as among-populations phenotypic variability assessments (e.g. based on morphological or stoichiometric traits), or surveys aimed at capturing how socio-economic activities and perceptions might be fuelling the spread of IAS in a given ecosystem may be thus necessary to adequately reveal pathways that might remain obscure when solely using genetic approaches.

Table III.S1 Populations of Faxonius limosus with information about lakes (Code, date of Creation, Latitude, Longitude and their level of fishery Management) and genetic analyses (sampling sizes (N), mean allelic richness (AR), expected heterozygosity (Hexp), mean private allelic richness (PA), mean genetic uniqueness (FstUNI) and mean Garza-Williamson statistic (GW)). A minimum sample size of 11 was considered for rarefaction procedures to obtain AR and PA estimates. The number of microsatellite loci (from a total of 8 polymorphic loci at the meta-population scale) monomorphic at the population level is also reported (NMONO).

Code

Creation Then, we demonstrated that P. clarkii trait variations in body morphology and stoichiometry were associated with both ecological and historical determinants (i.e. predation pressure, intraspecific invasion and invasion age), and morphological traits in F. limosus varied with ecological factors only (i.e. predation pressure and interspecific competition). Finally, we highlighted that different combinations of neutral and adaptive processes shaped the phenotypic variability in the two species, with a higher contribution of adaptive processes in F. limosus. Overall, these results indicated that F. limosus has already gone through local adaptation in the meta-population while this has not yet occurred for P. clarkii which was introduced later. This highlighted that these two invasive species might have contrasting effects across ecological scales.

Introduction

Intraspecific variability is increasingly studied within a multidisciplinary approach combining both population genetics and functional ecology, hence fostering our capacity to understand patterns of biodiversity [START_REF] Vellend | Drawing ecological inferences from coincident patterns of population-and community-level biodiversity[END_REF][START_REF] Mims | Traits-based approaches support the conservation relevance of landscape genetics[END_REF]. Such multi-facetted integrative studies highlight the eco-evolutionary processes underlying intraspecific variability patterns at multiple organizational levels (e.g. population, community or landscape levels [START_REF] Hendry | Evolutionary principles and their practical application[END_REF][START_REF] Lowe | Population genetics and demography unite ecology and evolution[END_REF], which can cause a heterogeneous distribution of intraspecific variation across ecological scales [START_REF] Mcgill | Exploring predictions of abundance from body mass using hierarchical comparative approaches[END_REF][START_REF] Messier | How do traits vary across ecological scales? A case for trait-based ecology[END_REF]Evangelista et al., 2019a). These patterns generally result from (i) adaptive processes (e.g. selection, plasticity)

under environmental gradients (i.e. linked to spatio-temporal dynamics of organisms and ecosystems; [START_REF] Holt | Analysis of adaptation in heterogeneous landscapes: implications for the evolution of fundamental niches[END_REF][START_REF] Ackerly | Community assembly, niche conservatism, and adaptive evolution in changing environments[END_REF][START_REF] Araújo | The ecological causes of individual specialisation[END_REF][START_REF] Prunier | The relative contribution of river network structure and anthropogenic stressors to spatial patterns of genetic diversity in two freshwater fishes: a multiple-stressors approach[END_REF], and from (ii) neutral processes (e.g. genetic drift) arising during range expansions (i.e. through surfing mutations and/or demographic processes like founder effects and population bottlenecks; [START_REF] Klopfstein | The fate of mutations surfing on the wave of a range expansion[END_REF][START_REF] Excoffier | Surfing during population expansions promotes genetic revolutions and structuration[END_REF]Bélouard et al., 2019). Because intraspecific variability can impact ecosystem functioning (Des [START_REF] Roches | The ecological importance of intraspecific variation[END_REF]Raffard et al., 2019b;[START_REF] Blanchet | A river runs through it: the causes, consequences, and management of intraspecific diversity in river networks[END_REF], through different contributions of individuals to trophic interactions, ecosystem productivity, nutrient cycling and/or through ecosystem engineering [START_REF] Harmon | Evolutionary diversification in stickleback affects ecosystem functioning[END_REF][START_REF] Bassar | Direct and indirect ecosystem effects of evolutionary adaptation in the Trinidadian guppy (Poecilia reticulata)[END_REF], there is a need to understand how it may vary across spatial and temporal scales.

In the context of biological invasions, intraspecific variability characterization may be helpful for predicting the ecosystem consequences of invasive individuals, which can intrinsically have important ecological effects [START_REF] Lockwood | Invasion Ecology[END_REF]. For example, ecological effects induced by sexual dimorphism can be modulate by sex-ratio variations [START_REF] Fryxell | Sex ratio variation shapes the ecological effects of a globally introduced freshwater fish[END_REF].

Biological invasions can be viewed as filtering processes during which invasive individuals pass through a succession of stages and of environmental filters [START_REF] Lockwood | Invasion Ecology[END_REF]Blackburn et al., 2011). The resulting founder effects and the adaptation of successful individuals to novel environments can lead to phenotypic differentiation between populations at the core of the invasion and those at the front, hence following the colonization gradient [START_REF] Huey | Rapid evolution of a geographic cline in size in an introduced fly[END_REF][START_REF] Strubbe | Niche conservatism in non-native birds in Europe: niche unfilling rather than niche expansion[END_REF]Juette et al., 2014). In recently established populations (i.e.

toward the invasion front), individuals may thus exhibit a higher range of phenotypic characteristics (i.e. high intraspecific variability) compared to populations established earlier and that have already experienced changes in population size and adaptation to local environments [START_REF] Aubret | Genetic assimilation and the postcolonization erosion of phenotypic plasticity in Island Tiger Snakes[END_REF][START_REF] Gutowsky | Intra-population variability of life-history traits and growth during range expansion of the invasive round goby, Neogobius melanostomus[END_REF][START_REF] Rey | Adaptation to global change: a transposable element-epigenetics perspective[END_REF]. The phenotypic variability may also be shaped locally by spatio-temporal variations of habitat characteristics (e.g. available trophic resources), abiotic environmental conditions, and the presence of natural enemies and/or competitors [START_REF] Mack | Biotic invasions, causes, epidemiology, global consequences and control[END_REF][START_REF] Shea | Community ecology theory as a framework for biological invasions[END_REF][START_REF] Kinnison | Eco-evolutionary vs. habitat contributions to invasion in salmon: experimental evaluation in the wild[END_REF]. Finally, the management of invaders might also lead to a change in their phenotypic traits, by selecting avoidance or smaller body-size phenotypes (Côté et al., 2014;Evangelista et al., 2015). All these potential sources of intraspecific variation make invasive species perfect candidates to study the effect of ecological determinants and evolutionary processes at short time-scales [START_REF] Hairston | Rapid evolution and the convergence of ecological and evolutionary time[END_REF][START_REF] Kinnison | Eco-evolutionary vs. habitat contributions to invasion in salmon: experimental evaluation in the wild[END_REF].

In this study, we investigated the patterns and the determinants of phenotypic variability of two invasive crayfish species exhibiting contrasting invasion histories and life-history traits that recently colonized our regional study area: the spiny-cheek crayfish, Faxonius limosus, which first occurred in 1988, and the red-swamp crayfish, Procambarus clarkii, which was first documented in 1995. Considering that they have distinct introduction histories and contrasting life histories, we expected to reveal contrasting patterns of phenotypic variability across the invaded landscape. Specifically, we first quantified -for each species-phenotypic variability (measured for morphological, trophic and stoichiometric traits) among populations, along with the distribution of its variance across different levels of within-species organization (i.e. individual, sex and population levels). Since F. limosus has been present in the study area for a longer period than P. clarkii, we expected that the spiny-cheek crayfish will display lower morphological variability at the individual level (i.e. within populations) compared to the population level (i.e. among populations). On the contrary, we expected a higher morphological variability in P. clarkii at the individual level compared to the population level,

as it has colonized the study area more recently. We also expected a high proportion of variance at sex level for both species, since they display both sexual dimorphism [START_REF] Chybowski | Morphometrics, fecundity, density, and feeding intensity of the spinycheek crayfish, Orconectes limosus (Raf.) in natural conditions[END_REF][START_REF] Malavé | Size, shape, and sex-dependent variation in force production by crayfish chelae[END_REF]. For both species, we expected a higher variance of trophic traits at the population level as they depend on local resources for generalist omnivorous species (Evangelista et al., 2019b), and we expected a higher variance of stoichiometric traits at the individual level since they rely mainly on ontogeny [START_REF] Bertram | Extensive natural intraspecific variation in stoichiometric (C:N:P) composition in two terrestrial insect species[END_REF]. Second, we investigated the environmental and historical determinants of each trait variability among populations for each species [START_REF] Vellend | Connections between species diversity and genetic diversity[END_REF]. We predicted that phenotypic variability would be mostly explained by environmental characteristics (i.e. lake productivity, predation pressure, the coexistence of the two crayfish species, anthropogenic pressure) for F. limosus, and mostly explained by the colonization history (invasion time-span) for P. clarkii, which might not have already undergone local adaptation due to the recent establishment of populations (< 20 years). Finally, we aimed at unravelling the mechanisms (neutral or adaptive)

underlying the phenotypic variability within and among populations [START_REF] Leinonen | QST-FST comparisons: evolutionary and ecological insights from genomic heterogeneity[END_REF].

Considering the lag time between both species' introductions in the study area, we expected that phenotypic divergences would be mainly explained by adaptive processes in F. limosus, which might already have experienced adaptation to local resources, and by neutral processes (i.e. genetic drift) in P. clarkii because of its recent establishment.

Material & methods

Study system and model species

The study was conducted in 23 gravel pit lakes ranging from 0.7 to 27 ha and located in a narrow geographical range: 12 to 55 km (Euclidean distance) away from Toulouse city along the Garonne River, in Southwestern France (Figure IV.1; see also [START_REF] Alp | Phenological response of a key ecosystem function to biological invasion[END_REF][START_REF] Zhao | Environmental determinants of fish community structure in gravel pit lakes[END_REF]. These lakes are disconnected from the hydrographic network unless during exceptional flood events, and their characteristics differ according to environmental and human pressure gradients: recent lakes are globally further away from Toulouse than mature lakes (i.e. more productive lakes), and under lighter anthropogenic pressure (i.e. fishing management; [START_REF] Zhao | Environmental determinants of fish community structure in gravel pit lakes[END_REF]. The invasion process is relatively recent in those lakes, since the presence of F. limosus and P. clarkii in the studied area were first documented in 1988 and in 1995, respectively [START_REF] Changeux | Évolution de la répartition des écrevisses en France Métropolitaine selon les enquêtes nationales mensées par le conseil supérieur de la pêche de 1977 à 2001[END_REF][START_REF] Magnier | L'enquête nationale sur les écrevisses[END_REF]. Our field observations revealed that gravel pit lakes colonization usually occurs rapidly, i.e. within a few months after gravel extraction has started. We henceforth computed a proxy of invasion time-span using the following formula:

Invasion time-span = sampling date -invasion date

where the sampling date is 2016, 2017 or 2018 and the invasion date is 1988 or 1995 for F. limosus and P. clarkii, respectively, for the lakes formed before the first recorded occurrence of each species. For the lakes formed after 1988 and 1995 we used the following formula:

Invasion time-span = sampling date -year of lake creation with the year of lake creation determined using aerial pictures (IGN 2019; see details in Table IV.1). Native from Northern America, P. clarkii and F. limosus are among the most invasive crayfish species worldwide [START_REF] Holdich | A review of the ever increasing threat to European crayfish from non-indigenous crayfish species[END_REF][START_REF] Filipová | Haplotype variation in the spinycheek crayfish Orconectes limosus: colonization of Europe and genetic diversity of native stocks[END_REF][START_REF] Oficialdegui | Unravelling the global invasion routes of a worldwide invader, the red swamp crayfish (Procambarus clarkii)[END_REF]. Both species strongly impact ecosystem functioning and native organisms through consumption (e.g. macroinvertebrates, fish, macrophytes; [START_REF] Correia | Shifts in aquatic macroinvertebrate biodiversity associated with the presence and size of an alien crayfish[END_REF][START_REF] Vojkovská | The diet of the spiny-cheek crayfish Orconectes limosus in the Czech Republic[END_REF], disease transmission [START_REF] Changeux | Évolution de la répartition des écrevisses en France Métropolitaine selon les enquêtes nationales mensées par le conseil supérieur de la pêche de 1977 à 2001[END_REF] and ecological engineering (e.g. burrowing activity, bioturbation; [START_REF] Correia | Burrowing behavior of the introduced red swamp crayfish Procambarus clarkii (Decapoda: Cambaridae) in Portugal[END_REF][START_REF] Holdich | The spiny-cheek crayfish, Orconectes limosus (Rafinesque, 1817) [Crustacea: Decapoda: Cambaridae], digs into the UK[END_REF]. The high invasiveness potential of P. clarkii might be partly attributable to its ability to disperse overland [START_REF] Kerby | Barriers and flow as limiting factors in the spread of an invasive crayfish (Procambarus clarkii) in southern California streams[END_REF][START_REF] Cruz | Colonization of freshwater habitats by an introduced crayfish, Procambarus clarkii, in Southwest Iberian Peninsula[END_REF][START_REF] Thomas | Terrestrial emigration behaviour of two invasive crayfish species[END_REF] and to its important agonistic behaviour [START_REF] Gherardi | Agonism and interference competition in freshwater decapods[END_REF]. Faxonius limosus tend to exhibit less aggressive interactions • VRA [START_REF] Chucholl | Aggressive interactions and competition for shelter between a recently introduced and an established invasive crayfish: Orconectes immunis vs. O. limosus[END_REF]Hudina & Hock, 2012) and has been reported overland on extremely rare occasions [START_REF] Puky | Invasive crayfish on land: Orconectes limosus (rafinesque, 1817) (decapoda: Cambaridae) crossed a terrestrial barrier to move from a side arm into the danube river at Szeremle, Hungary[END_REF]. To maximize their reproductive success, both species are suspected to combine sexual and asexual modes of reproduction (i.e. parthenogenesis; [START_REF] Yue | Discovery of four natural clones in a crayfish species Procambarus clarkii[END_REF][START_REF] Buřič | A successful crayfish invader is capable of facultative parthenogenesis: a novel reproductive mode in decapod crustaceans[END_REF][START_REF] Buřič | Reproductive plasticity in freshwater invader: from long-term sperm storage to parthenogenesis[END_REF]. In the studied system, previous studies highlighted the existence of substantial phenotypic variability (morphology, trophic ecology) among [START_REF] Jackson | Between-lake variation in the trophic ecology of an invasive crayfish[END_REF]Evangelista et al., 2019a) and within populations of P. clarkii (Raffard et al., 2017;[START_REF] Lang | Stable resource polymorphism along the benthic littoral-pelagic axis in an invasive crayfish[END_REF]. This suggests contrasted impacts of invasive individuals on ecosystem functioning among-populations of P. clarkii [START_REF] Alp | Phenological response of a key ecosystem function to biological invasion[END_REF]Evangelista et al., 2019b). No

• • • • • • • • • • • • • • • • • • • • • SOD SOC
study has yet focused on F. limosus intraspecific variability within our sampling area.

Sampling and environmental characteristics

Faxonius limosus and P. clarkii were sampled from mid-September to mid-October 2016-18 using pairs of baited traps (one cylindrical trap: 62cm x 34cm x 34cm, mesh size: 10mm; one rectangular trap: 95cm x 20cm x 20cm, mesh size: 4mm) set overnight (n = 12 traps) and during the day (n = 8 traps) in the littoral habitat. When needed, additional trapping, electrofishing (Deka 7000; Deka, Marsberg, Germany) and hand netting were performed along the shoreline to collect the desired number of adult crayfish, i.e. 24 individuals per species per lake, to robustly capture intraspecific variability in the studied phenotypic traits (e.g. [START_REF] Fourtune | Intraspecific genetic and phenotypic diversity: parallel processes and correlated patterns ?[END_REF]Evangelista et al., 2019a). Following capture, crayfish were sexed, measured for carapace length (± 0.01mm) and were euthanized on ice. A fresh muscle tissue sample from the abdomen was collected on each individual and stored in 70% ethanol at -20°C for subsequent genetic analyses, and each individual was placed in a labelled plastic bag and frozen in the laboratory. Stable isotope analyses were performed on an additional sample of abdominal muscle collected on each specimen after defrosting, rinsed with distilled water and oven-dried (60°C for 48 h).

During our crayfish sampling campaign, we also collected -for each lake -putative trophic resources of F. limosus and P. clarkii at three different locations representative of the littoral habitat of the lake. Specifically, periphyton (i.e. resource from aquatic origin) and poplar leaves (i.e. resource from terrestrial origin) were collected from the littoral since both species have a preference for vegetable diet at the adult stage [START_REF] Vojkovská | The diet of the spiny-cheek crayfish Orconectes limosus in the Czech Republic[END_REF][START_REF] Jackson | Between-lake variation in the trophic ecology of an invasive crayfish[END_REF]. Periphyton and poplar leaves samples were freeze-dried (-50°C for 5 days) and ovendried (60°C for 48h), respectively (further details available in [START_REF] Jackson | Between-lake variation in the trophic ecology of an invasive crayfish[END_REF]).

The same day, lake productivity was assessed by measuring the chlorophyll a concentration (µg.L -1 ) (with an AlgaeTorch device, BBE moldaenke GmbH, Germany) at three locations within each lake. These three values were averaged to account for within-lake variability in environmental conditions (Table IV.1). For each species, the abundance of crayfish was estimated in each lake as the number of individuals trapped over a 24-hour period (catch per unit effort (CPUE) expressed in ind. trap-1.hr-1; Table IV.1). The predation pressure in each lake was assessed as the biomass of predator fish trapped in a set of gillnets randomly distributed, over a 1-hour period (biomass per unit effort (BPUE) expressed in g.

gillnet-1.hr-1; Table IV.1; see further details in [START_REF] Zhao | Environmental determinants of fish community structure in gravel pit lakes[END_REF][START_REF] Lang | Stable resource polymorphism along the benthic littoral-pelagic axis in an invasive crayfish[END_REF].

For each lake, the level of anthropogenic pressure was assessed using management type as a proxy: private, communal and federal lakes were considered under low (coded "1"), medium

("2"), and strong ("3") anthropogenic pressure, respectively (Table IV.1). Faxonius limosus and P. clarkii coexisted in eleven lakes (i.e. sympatric populations) and were isolated in one lake for F. limosus and eleven lakes for P. clarkii (i.e. allopatric populations; Table IV.1).

Morphological, stable isotope and stoichiometric analyses

The morphological variation of crayfish body was analysed using a geometric morphometric technique [START_REF] Zelditch | Geometric morphometrics for biologists : a primer[END_REF] based on landmark analysis. Following Evangelista et al., (2019a) 19 homologous landmarks were digitized on F. limosus and P. clarkii individuals (i.e. cephalothorax and abdomen) using TpsDig2 v.2.17 [START_REF] Rohlf | The tps series of software[END_REF]. To avoid any distortion bias, individuals were photographed dorsally directly after defrosting and before further proceeding. We used a full-Procrustes fit (FPF) implemented in Morpho J v.1.06d to analyse the digitized coordinates by superimposing individual shapes (i.e. to remove bias due to different sizes, positions and orientations among individuals; [START_REF] Klingenberg | MORPHO J: an integrated software package for geometric morphometrics[END_REF]. We used the products of the FPF (i.e. new Procrustes coordinates) and their centroid size (i.e. the square root of the summed squared distances of each landmark from their centroid) to characterize individuals.

Oven-dried muscle samples were ground to a fine powder and analysed for carbon (δ 13 C) and nitrogen (δ 15 N) stable isotopes at the Cornell Isotope Laboratory (COIL, New York). The terrestrial reliance (α) of crayfish was computed as: α = (δ 13 Ccrayfish -δ 13 Cbase1)/ (δ 13 Cbase1 -δ 13 Cbase2)

and the trophic position (TPcrayfish) of each individual was computed following the two-sources model (i.e. aquatic vs. terrestrial source) of [START_REF] Post | Using stable isotopes to estimate trophic position: models, methods, and assumptions[END_REF]:

TPcrayfish= TPbaseline + (δ 15 Ncrayfish -[δ 15 Nbase1 x α + δ 15 Nbase2 x (1-α)]) / 3.4
where baseline organisms are poplar leaves (base 1) and periphyton (base 2), TPbaseline = 1, and 3.4 is the fractionation coefficient between trophic levels [START_REF] Post | Using stable isotopes to estimate trophic position: models, methods, and assumptions[END_REF].

Finally, for stoichiometric analyses, guts were removed for each crayfish prior to freeze-drying (Christ Martin™ Alpha 1-4 Ldplus Freeze Dryer), and individuals (whole-body) were finely grounded with two successive grindings using a grinder (Waring WSG30E) and an oscillating ball mill (Retsch MM200). A subsample of ground crayfish was analysed for Carbon (% C)

and Nitrogen (% N) contents using an organic elemental analyser (Flash 2000 Thermofisher),

and a mineralized replicate subsample (121°C for 2 hours in sodium persulfate) was used to analyse dissolved Phosphorus contents (% P) using spectrophotometry (molybdate method; [START_REF] Parsons | A manual of chemical and biological methods for seawater analysis[END_REF]. All elemental ratios (C:N, C:P, N:P) are expressed as molar ratios.

Genetic analyses

DNA extraction, PCRs protocol

Faxonius limosus neutral genetic variation was assessed using 9 microsatellites selected from (2020). We extracted DNA from the abdomen muscle of crayfish using a modified saltextraction protocol [START_REF] Aljanabi | Universal and rapid salt-extraction of high quality genomic DNA for PCR-based techniques[END_REF]. Three optimized multiplexed sets of loci for P.

Genotyping, quality control and genetic variability assessment

We tested for the presence of null alleles and other potential genotyping errors with Microchecker v.2.2.3 [START_REF] Van Oosterhout | MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data[END_REF] at the sampling site level and for each locus. We then tested for the presence of significant deviations from Hardy-Weinberg equilibrium (HW) using Genepop v 4.0 [START_REF] Rousset | GENEPOP'007: a complete re-implementation of the GENEPOP software for Windows and Linux[END_REF] and for the presence of significant linkage disequilibrium among loci within populations with Fstat v2.9.3.2 [START_REF] Goudet | Fstat Vision (1.2): a computer program to calculate F-statistics[END_REF].

Levels of significance for HW tests were corrected with Bonferroni corrections. Finally, we tested the neutrality of the microsatellite loci we used using BayeScan v.2.1 [START_REF] Foll | A genome-scan method to identify selected loci appropriate for both dominant and codominant markers: a Bayesian perspective[END_REF]. We performed four independent Markov chain Monte Carlo (MCMC) analyses considering 20 pilot runs of 5,000 iterations per analysis, burning periods of 50,000 iterations and sample sizes of 10,000 (with thinning intervals of 50). We also considered prior odds for the neutral model equal to 10. The convergence of the four MCMC chains was verified visually and by conducting a Gelman and Rubin analysis [START_REF] Gelman | Inference from iterative simulation using multiple sequences[END_REF], using the R v.3.6.0 statistical software (R Core Team, 2018) and a modified script from Paz-Vinas et al., (2013) based on the packages 'boa' [START_REF] Smith | boa: an R Package for MCMC output convergence assessment and posterior inference[END_REF] and 'coda' [START_REF] Plummer | CODA: convergence diagnosis and output analysis for MCMC[END_REF]. We considered that chains reached convergence when values lesser than 1.1 were obtained [START_REF] Gelman | Data analysis using regression and multilevel/hierarchical models[END_REF]. We quantified genetic diversity within lakes using observed (Hobs) and expected (Hexp) heterozygosity, computed with Genetix v4.05 [START_REF] Belkhir | GENETIX 4.05, logiciel sous Windows TM pour la génétique des populations[END_REF], and allelic richness (AR), mean number of alleles per locus (NA), and Wright fixation indices (Fis), computed with Fstat v2.9.3.2 [START_REF] Goudet | Fstat Vision (1.2): a computer program to calculate F-statistics[END_REF]; see details in Supplementary Material SM1 and Appendix Table S1). The global genetic differentiation across lakes (Fst) and its 95% confidence interval were computed for each species, using Fstat v2.9.3.2 [START_REF] Goudet | Fstat Vision (1.2): a computer program to calculate F-statistics[END_REF].

Statistical analyses

Phenotypic variability

For each species, allometry effect on body shape variation was removed using a regression of the Procrustes coordinates against log10-transformed centroid sizes, which are a proxy of individuals' body sizes [START_REF] Klingenberg | Size, shape, and form: concepts of allometry in geometric morphometrics[END_REF]. Covariance matrix of the regression residuals was used to run two Principal Component Analyses (PCA), to assess the intraspecific body shape variation. All these analyses were implemented in Morpho J. For each species, the first two PC axes were subsequently used as morphological scores (PC1 and PC2 scores) to Linear models (LMs) were run using PC1 and PC2 scores, carapace length, trophic position, terrestrial reliance, C:N, C:P, and N:P ratios as response variables and "sex" and "population" as explanatory variables, to assess the phenotypic variations among populations and sexes for each species.

Variance partitioning

As phenotypic traits may vary according to individuals, their sex and their respective population [START_REF] Malavé | Size, shape, and sex-dependent variation in force production by crayfish chelae[END_REF]Evangelista et al., 2019a), analyses of variance component of PC1 and PC2 scores, carapace length, morphological scores, trophic position, terrestrial reliance, and C:N:P ratios were performed for each species using the "varcomp" function from the 'ape' R package (v.5.3, Paradis et al. 2004) to quantify the distribution of variance for each trait across intraspecific ecological scales. "Individual" level was nested within "Sex" level, and nested within "Population" level, i.e. the studied lake. Variance partitioning was computed on linear mixed models (LMMs) ("nlme" package v.3.1.142; [START_REF] Pinheiro | Linear and nonlinear mixed effects models[END_REF]). 95% confidence intervals of variance composition were computed using a bootstrap procedure based on 200 iterations.

Environmental determinants

To summarize lakes characteristics, a Multiple Factor Analysis (MFA) was performed on "productivity" (chlorophyll-a concentration in µg.L -1 ), "predation pressure" (BPUE in g.gillnet - 1 .hr -1 ), "anthropogenic pressure" ("1", "2", "3" for low, medium and strong anthropogenic pressure, respectively), "coexistence" (Yes or No for allopatric and sympatric populations, respectively), "P. clarkii abundance" and "F. limosus abundance" (CPUE in ind. trap -1 .hr -1 ).

The first and second MFA axes explained 36.8% and 27.7% of the total variance, respectively.

Positive values on the first axis were associated with coexistence of the two crayfish species (and negative values with non-coexistence), and increasing values were associated with increasing productivity, increasing abundance of F. limosus, and increasing anthropogenic pressure. Increasing values on the second axis were associated with increasing predation pressure and decreasing P. clarkii abundance (Figure IV.S2). These two axes were used as synthetizing explanatory variables ("environmental variables 1 and 2") in the subsequent analyses.

LMMs were run to assess the effect of environmental characteristics (environmental variable 1, environmental variable 2) and the effect of the invasion time-span, on PC1 and PC2 morphological scores, trophic position, terrestrial reliance, C:N:P ratios, using "population" as random effect for each species (n = 501 and n = 256 for P. clarkii and F. limosus, respectively). For each full model, interactions were removed when non-significant using a backward procedure. Type II "Anova" implemented in the 'car' R package (v.3.0.5; Fox & Weisberg ( 2019)) was used to test the significance of each factor.

Neutral vs. adaptive processes

To identify the neutral or adaptive character of the processes underlying the phenotypic variability among sympatric populations of P. clarkii and F. limosus (n = 11), we compared neutral genetic (Fst) and phenotypic (Pst) differentiation within each species [START_REF] Leinonen | Contrasting patterns of body shape and neutral genetic divergence in marine and lake populations of threespine sticklebacks[END_REF]. Pst was computed for morphology, diet and stoichiometry as:

PstX = σ 2 betweenpops / (σ 2 betweenpops+ 2h 2 σ 2 withinpop)
where σ 2 is the variance of the phenotypic trait X (i.e. carapace length, morphological scores from PC1 and PC2 axis, trophic position, terrestrial reliance or C:N:P ratios) and h 2 is the heritability of X defined as the proportion of phenotypic variance with a genetic origin, set to 0.5 to avoid overestimating Pst [START_REF] Lutz | Estimation of heritabilities for growth, body size, and processing traits in red swamp crawfish, Procambarus clarkii (Girard)[END_REF][START_REF] Leinonen | Contrasting patterns of body shape and neutral genetic divergence in marine and lake populations of threespine sticklebacks[END_REF]. Traits evolve neutrally when Pst and Fst are equal, while different Pst and Fst imply adaptive processes (adaptive phenotype divergence for Pst > Fst, or a homogenizing adaptation if Pst < Fst). For each lake, the global phenotypic uniqueness was computed as the mean population-specific

Pst estimates of all traits (i.e. analogous to genetic uniqueness). All analyses were performed using the R v.3.6.0 statistical software (R Core Team, 2018).

Results

Phenotypic variability

We found high population-and sex-dependent morphological variations for both species (Figure IV.2; Table IV.S2). Concerning P. clarkii, morphological traits (PC1 and PC2 scores, carapace length) were significantly different among populations and between sexes (Appendix Table S2). More specifically, females had lower PC1 scores and higher PC2 scores than males, indicating that females had streamlined body compared to males, and they displayed higher carapace length than males (mean = 46.42 ± 0.30 SE and mean = 45.83 ± 0.38 SE, respectively; F1,478 = 14.454, P < 0.001). Concerning F. limosus, the interaction between sex and population effects on PC2 scores and carapace length was significant (interaction termPC2 score: F11,232 = 2.988, P < 0.001; interaction termCarapace length: F11,232 = 2.359, P = 0.009; Appendix Table S2). This indicated that the extent of sexual dimorphism in F. limosus varied between populations. Trophic traits (trophic position and terrestrial reliance) varied significantly between populations for both species (Table S2; Figure IV.3). Sex tended to have an effect on trophic position for F. limosus (F1,243 = 3.861, P = 0.051), with males displaying slightly higher trophic position than females (mean = 3.04 ± 0.05 SE and mean = 3.03 ± 0.03 SE, for males and females, respectively). Stoichiometric traits (C:N:P ratios) were highly context-dependent for P. clarkii and F. limosus: the interaction between sex and population was significant in all models except for N:P ratio in P. clarkii, which differed significantly among populations (F21,478 = 13.162, P < 0.001; Table IV .S2,Figure IV.4) and between sexes (F1,478 = 11.367, P < 0.001; Table IV.S2). Females had higher body N:P than males (mean = 12.87 ± 0.13 SE and mean = 12.66 ± 0.16 SE, for males and females, respectively).

Variance partitioning

For P. clarkii, morphological traits variations were higher at the individual level (67%, 62% and 75% of the variance for carapace length, PC1 and PC2 scores, respectively; Figure IV.5 a).

For F. limosus, two morphological traits variations were higher at the population level (47% and 72% for carapace length and PC1 scores, respectively), while PC2 scores variations were higher at sex and individual levels (48% and 47 %, respectively;

Environmental determinants

For morphological traits in P. clarkii, we only found predictors for PC2 scores. PC2 scores divergences were significantly explained by the invasion time-span (LMM, F1,18.8= 10.440, P = 0.005) and the environmental variable 2 (LMM, F1,17.4= 19.633, P < 0.001; Table IV Specifically, the carapace length of individuals increased with increasing predation pressure and decreasing abundance of P. clarkii. For the two species, there was no evidence for an association between trophic traits of individuals and historical or environmental determinants.

For P. clarkii, there was a significant effect of invasion time-span on C:P and N:P ratios of individuals (LMM, F1,18.6 = 10.433, P= 0.005 and LMM, F1,18.6 = 8.695, P= 0.008, respectively;

Table IV.S3). Specifically, C:P and N:P ratios of crayfish body decreased with increasing invasion time-span. There was also a significant effect of environmental variable 2 on N:P ratio (LMM, F1,17.6 = 4.640, P= 0.045; Table IV.S3). N:P ratio increased in P. clarkii individuals with increasing predation pressure and decreasing abundance of conspecifics. We detected no environmental or historical determinants neither for C:N ratio for P. clarkii, nor for all stoichiometric traits for F. limosus.

Neutral vs. adaptive processes

There was a global genetic differentiation among the studied lakes for P. clarkii (Fst = 0.213, CI95%: 0.191 -0.237) and for F. limosus (Fst = 0.209, CI95%: 0.077 -0.221). For P. clarkii, Pst for morphological traits and stoichiometric traits did not differ from Fst. This indicated that morphological and stoichiometric variations were due to neutral processes. Trophic position and terrestrial reliance variations were shaped by adaptive processes in P. clarkii, since their

Discussion

This study stresses the importance to investigate intraspecific trait variations across different ecological scales in invasive species to fully understand their ecological effects. Our results demonstrate that both F. limosus and P. clarkii display high intraspecific phenotypic variability (i.e morphological, trophic and stoichiometric traits) within and among populations, and this was despite a moderate and low genetic variability for P. clarkii and F. limosus, respectively.

We also highlighted a sexual dimorphism in both species, which was more pronounced in F. limosus. As expected, variance in morphological traits was mainly explained at the individual level in P. clarkii and at the population level in F. limosus. Trophic traits were mainly explained at the population level and stochiometric traits were mainly explained at the individual level for both species. Different factors explained the intraspecific variability of each species. For P. clarkii, morphological and stoichiometric traits were determined by both historical and environmental biotic determinants. For F. limosus, morphology of individuals varied with environmental biotic conditions. Finally, we highlighted that different combinations of neutral and adaptive processes shaped the intraspecific variability of F. limosus and P.

clarkii. Globally, as expected, the relative importance of adaptive processes underlying the intraspecific variability in F. limosus was stronger compared to P. clarkii.

Phenotypic variability and variance partitioning

As expected, morphological traits variations were mainly explained at the individual level (within population) and at the population level (among populations) for P. clarkii and F. limosus, respectively. This suggested that the fittest phenotypes might have been selected over time for F. limosus within populations, contrary to P. clarkii, which has been more recently established. Our results revealed the existence of sexual dimorphism in morphological and stoichiometric traits for both crayfish species [START_REF] Chybowski | Morphometrics, fecundity, density, and feeding intensity of the spinycheek crayfish, Orconectes limosus (Raf.) in natural conditions[END_REF][START_REF] Loureiro | Red swamp crayfish : biology, ecology and invasion -an overview[END_REF][START_REF] Malavé | Size, shape, and sex-dependent variation in force production by crayfish chelae[END_REF], a dimorphism that seems to be associated with a trophic differentiation in F. limosus. Morphological differentiation between sexes supported the results from other studies that have explored morphological dimorphism on these two species: females displayed an elongated abdomen at equal-size compared to males, as a result of carrying eggs under the abdomen [START_REF] Chybowski | Morphometrics, fecundity, density, and feeding intensity of the spinycheek crayfish, Orconectes limosus (Raf.) in natural conditions[END_REF][START_REF] Wang | Length-weight and chelae length-width relationships of the crayfish Procambarus clarkii under culture conditions[END_REF]. C:N:P composition of crayfish body is due to the balance between assimilation of elements from their environment, and excretion and egestion processes. The sexual dimorphism in stoichiometric traits might be due to a differentiated elemental requirements in females for egg productions [START_REF] Faerøvig | Allocation strategies in crustacean stoichiometry: the potential role of phosphorus in the limitation of reproduction[END_REF].

For both species, stoichiometric traits and trophic traits seem highly context-dependent, suggesting that variability in the elemental composition of crayfish resulted from a strong environmental pressure due to local bioavailability of nutrients or contrasted trophic resources among populations. The great trophic traits variance at the population level highlighted the opportunistic omnivorous diet of P. clarkii and F. limosus, which rely on available trophic resources [START_REF] Gutiérrez-Yurrita | Diet of the red swamp crayfish Procambarus clarkii in natural ecosystems of the Doñana National Park temporary fresh-water marsh (Spain)[END_REF][START_REF] Correia | Food choice by the introduced crayfish Procambarus clarkii[END_REF][START_REF] Vojkovská | The diet of the spiny-cheek crayfish Orconectes limosus in the Czech Republic[END_REF]. However, although the variation of the stoichiometric traits at the population level was notable (i.e. due to differences in available nutrients; El-Sabaawi et al., 2012b, 2012a), the major part of the variance was observed at the individual level for both species, which might be partly due to maturity and ontogenetic differences between individuals [START_REF] González | Exploring patterns and mechanisms of interspecific and intraspecific variation in body elemental composition of desert consumers[END_REF]. Variations in the elemental composition can be considered as physiological plasticity, which may be reversible at relatively short time scales compared to morphological plasticity, which is fundamentally driven by physiological processes, but is more likely to be permanent [START_REF] Bradshaw | Evolutionary significance of phenotypic plasticity in plants[END_REF]. Heterotrophic organisms' capacity to maintain their elemental composition in various environments when feeding on different resources' elemental composition is supposed to be high [START_REF] Sterner | Ecological stoichiometry: The biology of elements from molecules to the biosphere[END_REF]. Our results highlight the non-strict homeostasis of P. clarkii and F. limosus. The high differences at the individual level suggest that individuals may have strongly different effects on the ecosystem functioning (i.e. through different excretion and egestion rates; [START_REF] Vanni | Predicting nutrient excretion of aquatic animals with metabolic ecology and ecological stoichiometry: a global synthesis[END_REF]).

Environmental determinants

As expected, we found that morphological variations (carapace length) were explained by environmental characteristics for F. limosus, which might have undergone local adaptation.

Body size adaptations generally maximize foraging efficiency and constrain the body-size distribution of organisms in the food-web in return [START_REF] Lundberg | Optimal body size and resource density[END_REF][START_REF] Woodward | Body size and predatory interactions in freshwaters: scaling from individuals to communities. Body Size: the structure and function of aquatic ecosystems[END_REF]. Here, carapace length of F. limosus individuals increased with increasing predation pressure and decreasing interspecific competition (i.e. through density-dependent processes, [START_REF] Atkinson | Life histories and body size. Body Size: The Structure and Function of Aquatic Ecosystems[END_REF]. Larger individuals might have been selected over time since they might be less vulnerable to predation pressure through gape limitation [START_REF] Garvey | Scaledependent associations among fish predation, littoral habitat, and distributions of crayfish species[END_REF]. Concerning P. clarkii, our results highlighted that both colonization history (invasion time-span) and environmental biotic determinants (predation pressure and abundance of P.

clarkii) explained morphological variations, indicating that strong environmental pressure can actually rapidly lead to phenotypic variations in red-swamp crayfish, following its establishment (< 20 years; Evangelista et al., 2019a;[START_REF] Lang | Stable resource polymorphism along the benthic littoral-pelagic axis in an invasive crayfish[END_REF]. Specifically, our results suggest that P. clarkii individuals with an elongated rostrum, a shortened cephalothorax and a longer abdomen (i.e. deeper muscle involved in walking, [START_REF] Takahata | Positional orientation determined by the behavioural context in Procambarus clarkii Girard (Decapoda: Macrura)[END_REF] are likely to disperse easily overland, and to colonize new environments. This remains to be tested using quantitative genetics, by conducting a common garden study on genetically based phenotypic traits associated with fitness during range expansion [START_REF] Keller | History, chance and adaptation during biological invasion: separating stochastic phenotypic evolution from response to selection[END_REF].

In P. clarkii, stoichiometric traits variations were also explained by colonization history (invasion time-span) due to its recent establishment, and environmental biotic determinants (predation pressure and abundance of P. clarkii). C:P and N:P variations are likely due to P variations since C and N contents are relatively uniform in the different classes of molecules and cellular structures in organisms [START_REF] Sterner | Ecological stoichiometry: The biology of elements from molecules to the biosphere[END_REF]. Elemental composition variations in crayfish might be due to ontogeny differences, or differences of resource quality within the ecosystem (e.g. high N:P ratio in prey could lead to higher N:P ratio in consumer; [START_REF] Salanon | Variabilité et déterminants de la composition élémentaire d'espèces animales d'eau douce[END_REF]. Variations in C:P and N:P ratios in food resources between recent and old established populations might be due to lake eutrophication (%P increases with the invasion time span which is correlated to the age of lakes). However, we failed to detect the environmental and historical determinants of stoichiometric variability in F. limosus. This suggests that underlying determinants for this species are different.

Surprisingly, we failed to detect the determinants driving trophic traits variations for both crayfish species, and this is certainly because local resource availability in each lake was not considered in our models. A previous study on the same area found that body size, conspecifics abundance and lake size and productivity mediated the trophic ecology of P.

clarkii [START_REF] Jackson | Between-lake variation in the trophic ecology of an invasive crayfish[END_REF]. The relationship between environmental conditions and trophic traits of crayfish might also have been not detected because we studied lakes large enough to reduce competition and predation pressures and increase resource availability [START_REF] Stenroth | The influence of productivity and width of littoral zone on the trophic position of a largebodied omnivore[END_REF][START_REF] Jackson | Between-lake variation in the trophic ecology of an invasive crayfish[END_REF].

Neutral vs. adaptive processes

A combination of adaptive and neutral processes shaped the phenotypic variability within F. limosus and P. clarkii. As expected, neutral processes mostly shaped morphological and stoichiometric traits variations for P. clarkii, which has been established more recently in our study area. Trophic traits variations were due to adaptive processes, supporting our previous interpretation: this opportunistic generalist species relies on available trophic resources, constrained by the environment. Surprisingly, for F. limosus, adaptive and neutral processes contributed equally to the variations in each group of traits (i.e. morphological, trophic and stoichiometric traits). Results of Fst/Pst comparisons might be biased for F. limosus, since Fst values were relatively high between populations in the study area even though genetic diversity for this species was very low, probably due to a combination of historical (all European populations descend from a very low number of individuals introduced in Poland in 1890; [START_REF] Filipová | Haplotype variation in the spinycheek crayfish Orconectes limosus: colonization of Europe and genetic diversity of native stocks[END_REF] and biological factors. Indeed, the species was reported to perform facultative parthenogenesis in captivity, although this remains to be confirmed in the wild [START_REF] Buřič | A successful crayfish invader is capable of facultative parthenogenesis: a novel reproductive mode in decapod crustaceans[END_REF]. This differentiation might be due to the differential effects of genetic drift (stochastic fixation of different alleles in different lakes) among lakes following the founder effects produced when lakes are invaded. But if there are some limitations to Fst/Pst comparisons (Hendry 2002, Edelaar et al. 2011), Pst for a given trait are comparable between both species. As we expected, we found that the relative importance of adaptive processes shaping the phenotypic variability was greater in F. limosus, which has been established in our study area before P. clarkii and might have already experienced local adaptation. It is worth noting that P. clarkii is an early colonizer in our study area but this has not been observed for F. limosus (Cucherousset, personal observations), hence, invasion time span might have been overestimated for F. limosus and adaptive processes might have occurred even more rapidly following the invasion for this species compared to P. clarkii. Monitoring

Fst and Pst at the population level overtime would be insightful for describing the succession of processes involved in phenotypic differentiation within and between species. Combined with the study of population dynamics, such approach would be relevant to develop local management of invasive species to counter their impacts across the meta-population.

Conclusion

We highlighted strong morphological, trophic and stoichiometric variations among and within populations from two co-occurring invasive species, and more importantly, we found contrasting distribution of variance for each trait across three ecological scales (sex, individual, population), depending on the species. This suggests that invasive individuals have highly diverse impacts on ecosystem functioning even at small geographical scales, supporting previous findings (Phillips & Shine, 2006b;Juette et al., 2014;Evangelista et al., 2019b), and that these impacts differ depending on the considered ecological scale and on the considered species. It is of high importance to improve our understanding of the ecological and evolutionary mechanisms that shape genetic and phenotypic variations of invasive species because it can inform us on many relevant features such as their resistance to disturbance (i.e. global changes, removal attempt), their ability to expand their range and their potential impacts on ecosystem functioning Table IV.S1 Genetic diversity of Faxonius limosus (based on 8 microsatellites) and Procambarus clarkii (based on 13 microsatellites) in the 11 lakes where the species co-occur. We quantified genetic diversity using allelic richness (AR), the mean number of alleles per locus (NA), and the fixation index (Fis) computed with with Fstat v2.9.3.2 [START_REF] Goudet | Fstat Vision (1.2): a computer program to calculate F-statistics[END_REF], and expected (Hexp) and observed (Hobs) heterozygosity, computed with Genetix v4.05 [START_REF] Belkhir | GENETIX 4.05, logiciel sous Windows TM pour la génétique des populations[END_REF].

Lake

Introduction

Intraspecific variability is now widely recognized as playing a crucial role in evolutionary and ecological processes [START_REF] Violle | The return of the variance: intraspecific variability in community ecology[END_REF][START_REF] Read | Accounting for the nested nature of genetic variation across levels of organization improves our understanding of biodiversity and community ecology[END_REF]. Genetic and/or phenotypic differences among conspecific individuals can have important implications for community structure and ecosystem functioning by mediating the intensity of bottom-up or top-down processes (see review in Des Roches et al., 2017;[START_REF] Závorka | Importance of harvest-driven trait changes for invasive species management[END_REF]. Biological invasions provide a unique opportunity to study intraspecific variability in recently established populations. Indeed, substantial trait and genetic variability among invasive individuals has been reported [START_REF] Forsman | Effects of genotypic and phenotypic variation on establishment are important for conservation, invasion, and infection biology[END_REF][START_REF] González-Suárez | Intraspecific trait variation is correlated with establishment success of alien mammals[END_REF], indicating that a high level of intraspecific variability can occur following the introduction stage (60 -100 years after establishment, e.g. [START_REF] Kinnison | Population-specific variation in body dimensions of adult chinook salmon (Oncorhynchus tshawytscha) from New Zealand and their source population, 90 years after introduction[END_REF][START_REF] Hendry | Rapid evolution of reproductive isolation in the wild: evidence from introduced salmon[END_REF][START_REF] Lankau | Interpopulation variation in allelopathic traits informs restoration of invaded landscapes[END_REF]. Because intraspecific variability can modulate the ecological effects of invasive individuals on ecosystem processes (Evangelista et al., 2017), quantifying the extent of intraspecific variability in invasive species, notably within-populations and across the invasion landscape, is therefore relevant for both applied and theoretical perspectives.

Resource polymorphism refers to within-population morphological divergences due to differences in habitat and trophic resource use [START_REF] Smith | Evolutionary significance of resource polymorphisms in fishes, amphibians, and birds[END_REF]. It involves the use of an underexploited ecological niche by some individuals of the population, associated with changes in functional traits due to new environmental conditions [START_REF] Sol | Ecological mechanisms of a resource polymorphism in Zenaida Doves of Barbados[END_REF][START_REF] Komiya | A novel resource polymorphism in fish, driven by differential bottom environments: an example from an ancient lake in Japan[END_REF]. Stable resource polymorphism is defined as the existence of discrete morphs with no genetic isolation, and is associated with high gene flow between morphs [START_REF] Smith | Evolutionary significance of resource polymorphisms in fishes, amphibians, and birds[END_REF]. When gene flow is limited, subsequent genetic isolation can occur among morphs, resulting in distinct subpopulations (Smith & Skúlason, 1996) (Figure V.1). In freshwater lentic ecosystems, resource polymorphism commonly occurs along the littoralpelagic axis [START_REF] Quevedo | Intrapopulation niche partitioning in a generalist predator limits food web connectivity[END_REF][START_REF] Faulks | Genetic and morphological divergence along the littoral-pelagic axis in two common and sympatric fishes : perch, Perca fluviatilis (Percidae) and roach, Rutilus rutilus (Cyprinidae)[END_REF]. Littoral and pelagic habitats have distinct environmental characteristics (e.g. resource diversity, predation pressure, habitat structure, competition) and individuals using these distinct habitats often display significant morphological differences associated with trophic niche partitioning [START_REF] Svanbäck | Intraspecific competition drives multiple species resource polymorphism in fish communities[END_REF][START_REF] Bartels | Water transparency drives intrapopulation divergence in eurasian perch (Perca fluviatilis)[END_REF][START_REF] Faulks | Genetic and morphological divergence along the littoral-pelagic axis in two common and sympatric fishes : perch, Perca fluviatilis (Percidae) and roach, Rutilus rutilus (Cyprinidae)[END_REF][START_REF] Marklund | Asymmetrical habitat coupling of an aquatic predator -The importance of individual specialization[END_REF]. Additionally, genetic differences between littoral and pelagic morphs can occur due to assortative mating [START_REF] Robinson | Genetic variation and phenotypic plasticity in a trophically polymorphic population of pumpkinseed sunfish (Lepomis gibbosus)[END_REF]. Studying resource polymorphism could therefore provide new insights into an underexplored aspect of phenotypic variability within freshwater invasive species (but see [START_REF] Yonekura | Trophic polymorphism in introduced bluegill in Japan[END_REF][START_REF] Huey | Using invasive species to study evolution: case studies with Drosophila and Salmon. Species invasions: insights into ecology, evolution and biogeography[END_REF][START_REF] Davidson | Do invasive species show higher phenotypic plasticity than native species and, if so, is it adaptive? A meta-analysis[END_REF][START_REF] Komiya | A novel resource polymorphism in fish, driven by differential bottom environments: an example from an ancient lake in Japan[END_REF], which can subsequently help understanding their ecological impacts. In the present study, we quantified the extent of resource polymorphism in populations of highly invasive red-swamp crayfish (Procambarus clarkii) across bentho-littoral and benthopelagic habitats (hereafter referred as littoral and pelagic habitats). In lakes, P. clarkii has been reported to preferentially occupy littoral habitats [START_REF] Gherardi | Invasive crayfish in Europe: the impact of Procambarus clarkii on the littoral community of a Mediterranean lake[END_REF], but has also been occasionally reported in the pelagic habitat [START_REF] Foster | Status of the Louisianan red swamp crayfish Procambarus clarkii Girard in Lake Naivasha, Kenya 1999-2003[END_REF]. We first aimed at quantifying the existence of variability in habitat use (littoral vs. pelagic) and at identifying its associated ecological determinants. We predicted that crayfish abundance in the pelagic habitat would increase with increased abundance of crayfish in the littoral habitat, decreased habitat availability (proportion of littoral habitat compared to proportion of pelagic habitat), increased time of invasion and decreased predation pressure. Then, we quantified morphological and trophic traits of individuals from the littoral and pelagic habitats. We predicted the existence of differences in body and chelae morphology functionally associated with differences in habitat structure and resources consumed (trophic position and origin of zooplankton samples were freeze-dried (-50°C for 5 days) and oven dried (60°C for 48h), respectively (further details available in [START_REF] Jackson | Between-lake variation in the trophic ecology of an invasive crayfish[END_REF]. Samples of crayfish and putative prey were collected in September-October (i.e. at the end of the growing season) to ensure that stable isotope analyses were representative of the trophic interactions occurring during this period.

Abundance of littoral and pelagic crayfish were calculated as the number of crayfish trapped over a 24-hour period in each habitat (Catch Per Unit Effort (CPUE) expressed in ind. trap -1 .hr - 1 , Table Appendix V.1). On the same day, fish community was sampled to assess predation pressure. Gillnets were set in the littoral (length: 20 m, height: 2.4 m; mesh size: 12, 20, 30, 60 mm, n = 4 to 6 depending on the lake size) and pelagic habitats (length: 25 m, height: 3.1 m; mesh size: 20 and 50 mm respectively, n = 2) following [START_REF] Zhao | Environmental determinants of fish community structure in gravel pit lakes[END_REF]. Fish species were determined and each specimen was measured for fork length (± 0.01 mm). For each fish species, the body mass of each fish was computed using length-weight relationships (Zhao et al., unpublished data). Predator biomass in each lake was then calculated as the biomass of predator fish trapped in gillnets over a 1-hour period biomass (Biomass Per Unit Effort Silurus glanis (> 200 mm FL). Because the studied lakes were relatively small and these predatory species are highly mobile (i.e. they feed on crayfish in both habitats; [START_REF] Garvey | Scaledependent associations among fish predation, littoral habitat, and distributions of crayfish species[END_REF], a global predation pressure for each lake was calculated. In four lakes, P. clarkii coexisted with the invasive spiny-cheek crayfish (Faxonius limosus) which was present only in 25% of the studied lakes and in low density (ind.trap -1 .hr -1 mean = 0.07 ± 0.05 SE). As this species was rare, we did not consider potential interspecific competition with P. clarkii as a key driver of their habitat use in our analyses. The surfaces of littoral (< 3 m deep) and pelagic (> 3 m deep) habitats were measured for each lake using bathymetry data (Appendix 1). A depth threshold of 3.0 m was used to separate littoral from pelagic habitats following [START_REF] Garvey | Scaledependent associations among fish predation, littoral habitat, and distributions of crayfish species[END_REF] and [START_REF] Ruokonen | Invasive crayfish increase habitat connectivity: a case study in a large boreal lake[END_REF]. The proportion of littoral habitat (%) was then calculated as the ratio of littoral habitat surface and total lake surface.

Morphological and stable isotope analyses

Each crayfish and its right chela were photographed dorsally directly after defrosting and before tissue samples were taken for stable isotope analyses. Pictures were analyzed for morphological variation using TpsDig2 v.2.17 [START_REF] Rohlf | The tps series of software[END_REF]. We used a geometric morphometric technique [START_REF] Zelditch | Geometric morphometrics for biologists : a primer[END_REF] based on landmark analysis that has been widely used to quantify shape variations of morphological structures along the littoral-pelagic axis (e.g. [START_REF] Quevedo | Intrapopulation niche partitioning in a generalist predator limits food web connectivity[END_REF][START_REF] Bartels | Water transparency drives intrapopulation divergence in eurasian perch (Perca fluviatilis)[END_REF][START_REF] Faulks | Genetic and morphological divergence along the littoral-pelagic axis in two common and sympatric fishes : perch, Perca fluviatilis (Percidae) and roach, Rutilus rutilus (Cyprinidae)[END_REF]. Here, we digitized 19 homologous landmarks on P. clarkii individual bodies (i.e. cephalothorax and abdomen)

following Evangelista et al., (2019a) and 7 landmarks on their chela propodus (adapted from [START_REF] Malavé | Size, shape, and sex-dependent variation in force production by crayfish chelae[END_REF]. For each morphological structure (i.e. body and chela), a Full Procrustes Fit (FPF) was then performed using Morpho J v.1.06d to obtain a global shape comparison by superimposing individual shapes and remove the bias due to different sizes, positions and orientations among individuals [START_REF] Klingenberg | MORPHO J: an integrated software package for geometric morphometrics[END_REF]. The deformation components (i.e.

landmark coordinates) obtained with each FPF were projected into two separate matrices to characterize whole-body and whole-chela shape using partial warps (i.e. non-uniform variation localized to particular regions of geometry) and uniform scores (i.e. uniform variation throughout the body or the chela) [START_REF] Zelditch | Geometric morphometrics for biologists : a primer[END_REF]. Using whole-body and whole-chela datasets, the centroid size of each individual morphological structure was also calculated as the square root of the summed squared distances of each landmark from their centroid and used as a proxy of individual body and chela size.

Stable isotope samples were ground to a fine powder and analyzed for carbon (δ 13 C) and nitrogen (δ 15 N) stable isotopes at the Cornell Isotope Laboratory (COIL, New York). The trophic position (TPcrayfish) of each individual was computed following Vander [START_REF] Vander Zanden | Comparing trophic position of freshwater fish calculated using stable nitrogen isotope ratios (δ 15 N) and literature dietary data[END_REF]:

TPcrayfish= TPbaseline + (δ 15 Ncrayfish -δ 15 Nbaseline) / 3.4

where baseline organisms are a mix of leaf litter (allochthonous primary producer) and periphyton (autochthonous primary producer) (TPbaseline = 1), δ 15 Nbaseline corresponds to the mean of δ 15 Nperiphyton and δ 15 Nlitter and 3.4 is the fractionation coefficient between trophic levels [START_REF] Vander Zanden | Comparing trophic position of freshwater fish calculated using stable nitrogen isotope ratios (δ 15 N) and literature dietary data[END_REF][START_REF] Post | Using stable isotopes to estimate trophic position: models, methods, and assumptions[END_REF]. The origin of resource use was assessed by quantifying the littoral reliance (LR: relative dietary contribution of littoral resources to each individual), with periphyton and zooplankton as baselines for littoral and pelagic habitats respectively, and following Vander [START_REF] Vander Zanden | Fishes as integrators of benthic and pelagic food webs in lakes[END_REF]: LRcrayfish = (δ 13 Ccrayfish-δ 13 Czooplankton) / (δ 13 Cperiphyton-δ 13 Czooplankton).

Regarding littoral reliance, zooplankton is the only group of primary consumers that was consistently collected in all studied lakes, and which could contributed to the diet of crayfish [START_REF] Correia | Food choice by the introduced crayfish Procambarus clarkii[END_REF][START_REF] Alcorlo | Feeding preferences and food selection of the red swamp crayfish, Procambarus clarkii, in habitats differing in food item diversity[END_REF]. We have considered that P. clarkii were not selective on zooplankton taxa, so the pooled samples have been analyzed even though zooplankton have varying trophic positions [START_REF] Matthews | Compositional and interlake variability of zooplankton affect baseline stable isotope signatures[END_REF].

Genetic analyses

Neutral genetic differentiations were assessed using 14 microsatellites. 10 microsatellites were selected from Belfiore & May (2000) (PclG04, PclG07, PclG15, PclG16, PclG17, PclG27, PclG28, PclG29, PclG32 and PclG48) and 4 additional microsatellites (PCSH0038, PCSH0005, PCSH0006, PCSH0089) were used, based on [START_REF] Jiang | Microsatellite marker identification from transcriptome derived sequences of the red swamp crawfish, Procambarus clarkii[END_REF]. DNA was extracted from the abdomen muscle of crayfish using a salt-extraction method [START_REF] Aljanabi | Universal and rapid salt-extraction of high quality genomic DNA for PCR-based techniques[END_REF]. Loci were amplified by Polymerase Chain Reaction (PCR) in a final volume of 10 μL, containing 10-20 ng of genomic DNA, 5 μL of QIAGEN® Multiplex PCR and locusspecific optimized combination of primers (see Table Appendix V.2). PCR was performed in a Mastercycler (Eppendorf®) under the following conditions: 15 min at 95°C followed by 35 cycles of 0.5 min at 94°C, 1.5 min at 56°C and 1 min at 72°C and finally followed by a 45 min final elongation step at 60°C (see Appendix 2 for the description of the multiplex used in this study). Amplified fragments were analyzed on an ABI PRISM 3730 capillary sequencer (Applied Biosystems, Foster City, USA) in the Génopole Toulouse Midi-Pyrénées. Allele size results were scored using GENEMAPPER v.4.0 (Applied Biosystems). Then, deviations from Hardy-Weinberg equilibrium (HWE) and linkage disequilibrium (LD) between all pairs of loci were tested using FSTAT v.2.9.3.2 [START_REF] Goudet | Fstat Vision (1.2): a computer program to calculate F-statistics[END_REF] and null alleles were tested using MICROCHECKER v.2.2.3 [START_REF] Van Oosterhout | MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data[END_REF]. Genetic diversity was quantified using observed (Ho) and expected (He) heterozygosity, Wright fixation indices FIS and allelic richness (AR), based on the minimum sampling size. The genetic differentiation (Fst) between littoral and pelagic individuals was calculated using FSTAT v.2.9.3.2 [START_REF] Goudet | Fstat Vision (1.2): a computer program to calculate F-statistics[END_REF]. No null alleles were detected in the genotyped loci. The number of alleles per locus ranged from 2 to 11 (Table V.1). We found no linking disequilibrium between pairs of loci. There was no evidence for any significant heterozygous deficit for the considered loci after Bonferroni correction, suggesting that all populations were at Hardy-Weinberg equilibrium.

Statistical analyses

To test the association between environmental conditions and the abundance of P. clarkii in the pelagic habitat of the 16 lakes, we performed a linear model (LM) using abundance of P.

clarkii in littoral habitat, predation pressure (predators' biomass), habitat availability (proportion of littoral habitat), time of invasion (expected date of lake invasion) and their twoway interactions as fixed effects. The full model was built and interactions were removed when non-significant using a backward procedure. Variance inflation factor (VIF) did not detect multicollinearity between predictors (VIF < 5) (R package "car" v. 3.0-0; [START_REF] Fox | car : companion to applied regression[END_REF].

Comparison of ecological and genetic characteristics between habitats were performed in 7 lakes where a sufficient number of individuals was collected in each habitat (mean number of individuals per habitat = 19.79 ± 0.8 SD; Table Appendix V.1). We used a linear mixed-model (LMM) with "carapace length" as response variable, "habitat" and "sex" as fixed effects, and "lake" as random effect to test for a significant difference of crayfish size between littoral and pelagic individuals. To remove potential allometric component of shape variation, partial warps scores were regressed against centroid sizes, using a pooled within-habitat regression in Morpho J [START_REF] Klingenberg | Size, shape, and form: concepts of allometry in geometric morphometrics[END_REF]. Regression residuals scores (for body and for chela) were analysed in two distinct Discriminant Function Analysis (DFA) implemented in Morpho J to determine if the morphology of individuals from the littoral and pelagic habitats differs significantly [START_REF] Klingenberg | MORPHO J: an integrated software package for geometric morphometrics[END_REF]. Each individual was thus characterized by a DFA morphological score for both body and chela along the littoral-pelagic axis. Sexual dimorphism is a potent agent of intraspecific morphological divergence [START_REF] Malavé | Size, shape, and sex-dependent variation in force production by crayfish chelae[END_REF] and this effect was assessed using a LMM with "DFA score" as response variable, "sex" and "habitat" and their interaction as fixed effects, and "lake" as random effect. When significant, the interaction was further investigated with post-hoc pairwise comparison of the estimated marginal means using the "emmeans" function in "emmeans" R package v.1.4.3.01 [START_REF] Lenth | emmeans: estimated marginal means, aka least-squares means[END_REF]. Because trophic resources use has been reported not to differ between sex in crayfish [START_REF] Gutiérrez-Yurrita | Diet of the red swamp crayfish Procambarus clarkii in natural ecosystems of the Doñana National Park temporary fresh-water marsh (Spain)[END_REF][START_REF] Pérez-Bote | Feeding ecology of the exotic red swamp crayfish, Procambarus clarkii (Girard, 1852) in the Guadiana River (SW Iberian Peninsula)[END_REF][START_REF] Houghton | Size-mediated, density-dependent cannibalism in the signal crayfish Pacifastacus leniusculus (Dana, 1852) (Decapoda, Astacidea), an invasive crayfish in Britain[END_REF], sex was not included in the subsequent trophic analyses. To test for the presence of resource polymorphism, we first used a LMM with "trophic position" as response variable and a generalized linear mixedmodel (GLMM) with "littoral reliance" as response variable, with each model including "habitat" and "lake" as fixed and random effects, respectively. The LMM was run using "lme4" R package v. 1.1-21 [START_REF] Bates | lme4: Linear mixed-effects models using Eigen and S4[END_REF]. Littoral reliance was a continuous variable bounded between 0 and 1 and the GLMM was thus run using a beta distribution in the "glmmTMB" R package v. 0.2.3 [START_REF] Magnusson | glmmTMB: generalized linear mixed models using template model builder[END_REF]. We then tested the association between individual morphology (body and chela DFA scores) and origin of resource use (i.e. littoral reliance) using a beta regression implemented in "betareg" R package v3.1-1 (Cribari-Neto & Zeilis, 2010).

For all models, residuals normality and homoscedasticity were checked using Q-Q plot and Tukey-Anscombe plot, respectively. Abundance of P. clarkii in pelagic habitat was squareroot transformed to conform with these assumptions.

Genetic and phenotypic differentiations were compared to determine the underlying process (neutral or adaptive process) explaining variability between littoral and pelagic individuals [START_REF] Leinonen | Contrasting patterns of body shape and neutral genetic divergence in marine and lake populations of threespine sticklebacks[END_REF]. We used a quantitative genetic approach based on Fst calculated using microsatellites as neutral genetic markers and the phenotypic equivalent Pst (i.e. used as a proxy of Qst for natural environments) was calculated for both morphology and diet as:

PstX = σ 2 betweenpops / (σ 2 betweenpops+ 2h 2 σ 2 withinpop)
where σ 2 is the variance of the phenotypic trait X (i.e. DFA scores, trophic position or littoral reliance) and h 2 is the heritability of X defined as the proportion of phenotypic variance with a genetic origin [START_REF] Leinonen | Contrasting patterns of body shape and neutral genetic divergence in marine and lake populations of threespine sticklebacks[END_REF]. Because we had no information on trait heritability, h 2 was set to 0.5 to avoid overestimating Pst (e.g. heritability estimates for the studied traits are close to 0.3 -0.5; [START_REF] Lutz | Estimation of heritabilities for growth, body size, and processing traits in red swamp crawfish, Procambarus clarkii (Girard)[END_REF]. When Pst and Fst are equal, considered traits evolve neutrally under genetic drift. A greater Pst than Fst implies an adaptive phenotype divergence while a higher Fst suggests a homogenizing adaptation. We estimated the between-habitats variance using LMMs ("lme4" R package v. 1.1-21) with the phenotypic traits as response variables, the intercept as a fixed effect and the "habitat" as a random effect. "Littoral reliance" was square-root transformed to improve the fit of the model. We computed 95% confidence interval (CI95%) for Pst, using bootstrapping procedure (Raffard et al., 2019a), while CI95% for Fst was implemented in FSTAT. All statistical analyses were performed using R v.3.4.4 (R Core Team, 2018).

Results

P. clarkii occurred in all littoral habitats, and was detected in the pelagic habitat of 75% of the sampled lakes. P. clarkii abundances within littoral and pelagic habitats were highly variable among lakes, ranging from 0.00 to 4.79 ind. trap -1 hr -1 in the littoral habitat and from 0.00 to 10.63 ind. trap -1 hr -1 in the pelagic ones (Table Appendix V.1). In the latter, crayfish abundance was significantly and positively related to the abundance of P. clarkii in the littoral habitat (LM, F1,10 = 38.90, P < 0.001). There was no significant effect of the proportion of littoral habitat (LM, F1,10 = 0.49, P = 0.500), predators' biomass (LM, F1,10 = 0.04, P = 0.856) and time of invasion (LM, F1,10 = 2.87, P = 0.121) on the abundance of P. clarkii in the pelagic habitat.

In the 7 lakes where P. clarkii was abundant in both littoral and pelagic habitats, sex ratio did not differ between littoral and pelagic habitats (t-test, t = 2.23, df = 6, P = 0.07; performed using all the crayfish captured). Carapace lengths differed significantly between females and males (LMM, F1,268 = 8.89, P = 0.003), with females displaying longer carapace lengths than males (mean ± SE = 49.14 ± 0.50 mm and 47.62 ± 0.41 mm respectively). There was no significant difference in carapace length between individuals from littoral and pelagic habitats (LMM, F1,268 = 0.65, P = 0.423; Figure Appendix V.3). However, individuals from each habitat differed significantly in body morphology (DFA; T-square = 80.31; P < 0.001). Specifically, individuals from littoral habitat had lower DFA scores than those from pelagic habitat (mean = -0.06 ± 0.11 SE and 0.62 ± 0.08 SE, respectively), indicating that littoral crayfish were characterized by stocky body and rostrum, while pelagic crayfish had a more streamlined body and rostrum (Figure V.2a). It is, however, interesting to note that the extent of morphological differences between littoral and pelagic individuals varied between lakes (Figure Appendix V.4). Even if females had higher DFA body scores than males (mean = 0.30 ± 0.09 SE and -0.24 ± 0.11 SE, respectively), the effect of sex alone did not affect body shape.

However, DFA scores were significantly affected by the effect of habitat (LMM, F1,268 =79.16, P < 0.001; as also seen with the DFA analysis) and this effect was sex-dependent (LMM, interaction term: F1,270 = 18.54, P = 0.004). Specifically, for both sexes, pelagic individuals had higher DFA body scores compared to littoral ones (Post-hoc tests, t ratio = -3.62, df = 268, P < 0.001 and t ratio = -8.59, df = 269, P < 0.001 for females and males respectively; Figure Trophic position of P. clarkii did not significantly differ between littoral (mean = 3.00 ± 0.05 SE) and pelagic (mean = 3.05 ± 0.05 SE) individuals (LMM, F1,268 = 2.96, P = 0.086;

Figures V.4a, Figure Appendix V.5
). However, littoral reliance of littoral individuals (mean = 0.35 ± 0.02 SE) was significantly higher than for pelagic individuals (mean = 0.33 ± 0.02 SE), supporting the existence of a differential niche use (GLMM, χ 2 = 7.50, df = 1, P = 0.006; There was no significant genetic differentiation between individuals from the littoral and pelagic habitats (littoral-pelagic global Fst = 0.000, CI95%: 0.000 -0.002 and ANOVA -He: P = 0.407; AR: P = 0.561) (Table V.1). Pst for body morphology and chela morphology were 0.364 (CI95%: 0.269 -0.457) and 0.152 (CI95%: 0.056 -0.275) respectively, and were significantly higher than Fst, indicating that morphological variations were due to adaptive divergent processes. Pst for trophic position and littoral reliance were 0.000 (CI95%: 0.000-0.0448) and 0.000 (CI95%: 0.000 -0.0542), respectively. There was no significant difference between Pst for trophic position and littoral reliance and the global Fst value, indicating that both trophic traits evolved under non-adaptive processes (i.e. genetic drift).

Figures V.4b

Discussion

Our results supported the existence of resource polymorphism within invasive species.

Indeed, we observed that morphological divergences between littoral and pelagic habitats were also associated with changes in the origin of the resource used by crayfish. This resource polymorphism might occur due to intraspecific competition since the abundance of pelagic crayfish was strongly and positively associated with the abundance of littoral crayfish.

There was no genetic differentiation between individuals from the two habitats, indicating that the resource polymorphism was stable (Figure V.1). Finally, we demonstrated that morphological divergences in body and chela shapes between habitats were driven by a divergent adaptive process, while difference in the origin of the resource use neutrally evolved under genetic drift. Although crayfish abundance was highly variable between lakes, the species occurred in the pelagic habitat of 75% of the studied lakes and was abundant in both littoral and pelagic habitats in 44% of the studied lakes. In addition, we found that increased pelagic abundance was associated with increased littoral abundance. This suggests that intraspecific competitive exclusion was a potential mechanism explaining the presence of crayfish in the pelagic habitat. Increased population density in the preferred littoral habitat of crayfish [START_REF] Nyström | Crayfish in lakes and streams: individual and population responses to predation, productivity and substratum availability[END_REF] can favor aggressiveness between conspecifics [START_REF] Gherardi | Agonism and interference competition in freshwater decapods[END_REF], limiting the access to shelters (e.g under cobble, tree trunks, macrophytes, rocks) and forcing some weak competitors to migrate to the pelagic habitat. Competitive exclusion may also explain morphological divergences between littoral and pelagic crayfish for both sexes, with stockierbodied and streamlined individuals occupying the littoral and pelagic habitats, respectively.

Although this remains to be tested experimentally, individuals with a stocky cephalothorax and rostrum and with longer chelae might have a competitive advantage compared to more streamlined individuals to occupy littoral shelters [START_REF] Stein | Selective predation, optimal foraging, and the predatory-prey interaction between fish and crayfish[END_REF].

Predation might also be a driver of morphological differences observed between the two habitats [START_REF] Stein | Selective predation, optimal foraging, and the predatory-prey interaction between fish and crayfish[END_REF][START_REF] Kershner | Effects of littoral habitat and fish predation on the distribution of an exotic crayfish, Orconectes rusticus[END_REF]. In the littoral habitat, stockier-bodied individuals might have an advantage to face predation pressure from both aquatic (i.e. fish) and terrestrial (i.e. birds) predators [START_REF] Davis | Activity patterns, behavioural repertoires, and agonistic interactions of crayfish: a non-manipulative field study[END_REF] by hiding and defending their shelters. In the pelagic habitat, streamlined individuals with more elongated abdomen might be more efficient to move in the muddy substrate and escape from predators via tail flipping [START_REF] Wine | The organization of escape behaviour in the crayfish[END_REF][START_REF] Patullo | The relationship between body size and the field potentials generated by swimming crayfish[END_REF]. Furthermore, streamlined bodies with thicker chelae might provide a defense against predators through gape limitation [START_REF] Englund | Habitat use by crayfish in stream pools: influence of predators, depth and body size[END_REF][START_REF] Garvey | Scaledependent associations among fish predation, littoral habitat, and distributions of crayfish species[END_REF][START_REF] Davis | Activity patterns, behavioural repertoires, and agonistic interactions of crayfish: a non-manipulative field study[END_REF]. As the extent of morphological differentiation between habitats differed between lakes (Figure Appendix V.4), it would be interesting to determine whether the extent of differences in environmental conditions between the littoral and the pelagic habitats drive the intensity of the morphological differentiation observed.

As expected, littoral individuals consumed more resources originating from the littoral habitat than pelagic individuals. Given the turnover rate of stable isotope values in crayfish muscle tissue (> 1 month; [START_REF] Carolan | Biokinetics and discrimination factors for δ 13 C and δ 15 N in the omnivorous freshwater crustacean, Cherax destructor[END_REF][START_REF] Glon | Comparison of 13 C and 15 N discrimination factors and turnover rates between congeneric crayfish Orconectes rusticus and O. virilis (Decapoda, Cambaridae)[END_REF], these findings indicate that the feeding activity of individuals occurs within their respective habitats. There was, however, no significant difference in trophic position between littoral and pelagic individuals. Trophic positions of 3 indicated that P. clarkii feed on more than one trophic level and are thus

F 0.1 PclG-48 R 0.1 PclG-17 F 0.1 PclG-17 R 0.1 PCSH0089 F 0.1 PCSH0089 R 0.1 PCSH0006 F 0.1 PCSH0006 R 0.1 PCSH0005 F 0.1 PCSH0005 R 0.1 PCR cycling conditions 95°C 94°C 56°C 72°C 60°C

Figure Appendix V.4

Frequency distribution of Procambarus clarkii body morphological scores obtained using a Discriminant Functional Analysis along the littoral-pelagic axis (nlittoral = 20, dark grey; npelagic = 20 except for lake J where npelagic = 17, blue) of the 7 gravel pit lakes. Note that the X-axis scale is different for Lake K.

Figure Appendix V.5

Stable isotopes values (δ 15 N and δ 13 C; ‰) of individuals Procambarus clarkii (circles) from littoral (dark grey) and pelagic (blue) habitats in the 7 gravel pit lakes. Black triangles and white squares represent periphyton and zooplankton in each lake, respectively. Note that the Y-axis scale for Lake K differs from the others.

Introduction

Biological invasions can induce impacts at multiple levels of biological organization [START_REF] Cucherousset | Ecological impacts of non-native freshwater fishes[END_REF]. Invaders interact with native organisms through competition, predation and hybridization [START_REF] Hasegawa | Effect of habitat components on competitive interaction between native white-spotted charr and introduced brown trout[END_REF][START_REF] Muhlfeld | Legacy introductions and climatic variation explain spatiotemporal patterns of invasive hybridization in a native trout[END_REF], and affect biotic processes (e.g. trophic cascades; [START_REF] Walsh | Invasive species triggers a massive loss of ecosystem services through a trophic cascade[END_REF] and abiotic conditions in recipient ecosystems through ecosystem engineering (e.g. habitat structure; [START_REF] Anderson | Ecosystem engineering by invasive exotic beavers reduces in-stream diversity and enhances ecosystem function in Cape Horn, Chile[END_REF]. Recent investigations have revealed the ecological role of intraspecific variability that can have major effects on ecosystem functioning (see Des [START_REF] Roches | The ecological importance of intraspecific variation[END_REF]Raffard et al., 2019b for review). This is particularly important for biological invasions because intraspecific variability (i) may favor species establishment along environmental gradients [START_REF] Moyle | Predicting invasion success: freshwater fishes in California as a model[END_REF][START_REF] González-Suárez | Intraspecific trait variation is correlated with establishment success of alien mammals[END_REF] and (ii) can modulate the ecological impacts of invasive species on native organisms and recipient ecosystems (Evangelista et al., 2015;[START_REF] Závorka | Importance of harvest-driven trait changes for invasive species management[END_REF]. Therefore, quantifying variability in invasive species across multiple functional traits is crucial to anticipate local, regional and global ecological consequences of invaders [START_REF] Mimura | Understanding and monitoring the consequences of human impacts on intraspecific variation[END_REF].

Functional traits are informative on how individuals respond to environmental fluctuations (response traits), and how they affect their environment (effect traits, [START_REF] Violle | Let the concept of trait be functional ![END_REF][START_REF] Díaz | Functional traits, the phylogeny of function, and ecosystem service vulnerability[END_REF]. For instance, morphological (e.g. body size, defense structures; [START_REF] Garvey | Evaluating how chela size influences the invasion potential of an introduced crayfish (Orconectes rusticus)[END_REF][START_REF] Smith | Physiological and morphological traits of exotic, invasive exotic, and native plant species in Tallgrass prairie[END_REF])) or behavioral (e.g. aggressiveness; [START_REF] Pintor | Differences in aggression, activity and boldness between native and introduced populations of an invasive crayfish[END_REF][START_REF] Polo-Cavia | Aggressive interactions during feeding between native and invasive freshwater turtles[END_REF] response traits are major in defining reproduction success, predatory defense or dominance of invasive individuals in recipient ecosystems. Invasive generalist consumers can directly impact food webs at multiple trophic levels and affect community dynamics, in comparison with specialized individuals [START_REF] Olden | Ecological and evolutionary consequences of biotic homogenization[END_REF][START_REF] Layman | Characterizing trophic ecology of generalist consumers: a case study of the invasive lionfish in the Bahamas[END_REF][START_REF] Schmitt | Feeding ecology of generalist consumers : a case study of invasive blue catfish Ictalurus furcatus in Chesapeake Bay, Virginia, USA[END_REF]. They also have important nutrient-mediated impacts (nutrients dynamics and bioavailability ; Evans-White & Lamberti, 2005; [START_REF] Usio | Alien vs. endemic crayfish: roles of species identity in ecosystem functioning[END_REF]. Holistic approaches are appropriate to apprehend the implication of multiple trait covariations on the role of organisms in ecosystems, and particularly, to unravel how response traits can infer ecological processes in return (Raffard et al., 2017;[START_REF] Diaz Pauli | Ecosystem consequences of multi-trait response to environmental changes in Japanese medaka, Oryzias latipes[END_REF]. Correlations among and between response and effect traits, which form syndromes, are common (e.g. [START_REF] Reale | Personality and the emergence of the pace-of-life syndrome concept at the population level[END_REF][START_REF] Dingemanse | Defining behavioural syndromes and the role of "syndrome deviation" in understanding their evolution[END_REF]Raffard et al., 2017). The most noticeable lifehistory trade-off relies on covariations of metabolism with life history traits and involves the cost of reproduction against survival [START_REF] Reale | Personality and the emergence of the pace-of-life syndrome concept at the population level[END_REF], which are crucial for the establishment of invasive species [START_REF] Kozák | The effect of interand intra-specific competition on survival and growth rate of native juvenile noble crayfish Astacus astacus and alien spiny-cheek crayfish Orconectes limosus[END_REF][START_REF] Burton | What causes intraspecific variation in resting metabolic rate and what are its ecological consequences[END_REF][START_REF] Lagos | Do invasive species live faster? Massspecific metabolic rate depends on growth form and invasion status[END_REF].

Recently, Raffard et al. (2017) demonstrated that response and effect traits do covary in the highly invasive the red swamp crayfish Procambarus clarkii to form a functional syndrome.

However, our understanding of the ecosystem implications of these syndromes is limited (but see Raffard et al., 2017;[START_REF] Diaz Pauli | Ecosystem consequences of multi-trait response to environmental changes in Japanese medaka, Oryzias latipes[END_REF]. Quantifying phenotypic syndrome (i.e. multitrait covariations) in invasive species, would help to fully understand inherent links between traits and functions of invaders, and their invasiveness potential.

Crayfish are one of the most introduced taxa worldwide and their impacts are challenging to predict because they are highly species and context-dependent [START_REF] Twardochleb | A global meta-analysis of the ecological impacts of nonnative crayfish[END_REF]Jackson et al., 2014). On many occasions, invasive crayfish have been reported to co-occur in their introduced area [START_REF] Chucholl | Aggressive interactions and competition for shelter between a recently introduced and an established invasive crayfish: Orconectes immunis vs. O. limosus[END_REF]Larson & Olden, 2013;[START_REF] Anastácio | Indicators of movement and space use for two co-occurring invasive crayfish species[END_REF].

For instance, P. clarkii and the spiny cheek crayfish Faxonius limosus, which are among the most widespread invasive crayfish species [START_REF] Filipová | Haplotype variation in the spinycheek crayfish Orconectes limosus: colonization of Europe and genetic diversity of native stocks[END_REF][START_REF] Oficialdegui | Unravelling the global invasion routes of a worldwide invader, the red swamp crayfish (Procambarus clarkii)[END_REF] coexist in gravel pit lakes in southwestern France [START_REF] Alp | Phenological response of a key ecosystem function to biological invasion[END_REF][START_REF] Jackson | Between-lake variation in the trophic ecology of an invasive crayfish[END_REF][START_REF] Lang | Stable resource polymorphism along the benthic littoral-pelagic axis in an invasive crayfish[END_REF]. These two species share similar features contributing to their invasion success:

a high fecundity, a rapid life cycle, and a great dispersal ability, in comparision with native species, and an opportunistic diet [START_REF] Renai | Predatory efficiency of crayfish: comparison between indigenous and non-indigenous species[END_REF][START_REF] Souty-Grosset | Atlas of crayfish in Europe. Patrimoines naturels 64[END_REF].

Nevertheless, they also differ in some important aspects: P. clarkii is generally more aggressive than F. limosus and display larger burrowing ability and thermal tolerance, which provides prior access to shelter and trophic resources and therefore, an advantage on direct competition [START_REF] Holdich | The spiny-cheek crayfish, Orconectes limosus (Rafinesque, 1817) [Crustacea: Decapoda: Cambaridae], digs into the UK[END_REF][START_REF] Capinha | Effects of climate change, invasive species, and disease on the distribution of native european crayfishes[END_REF][START_REF] Gherardi | Climate warming and the agonistic behaviour of invasive crayfishes in Europe[END_REF]. The functional roles of P. clarkii and F. limosus likely differ [START_REF] Gherardi | Understanding the impact of invasive crayfish[END_REF]. These co-occurring species, which display a high intraspecific variability, are the perfect candidates to study the structure of trait variations and covariations and related implications on ecosystem functioning [START_REF] Twardochleb | A global meta-analysis of the ecological impacts of nonnative crayfish[END_REF].

In the present study we aimed at quantifying functional trait variation and covariations in cooccurring P. clarkii and F. limosus by measuring a series of functional traits on individuals in an experimental context. First, we quantified interspecific differences in a suite of response (morphology, chela strength, growth rate, behavior, and metabolism) and effect (excretion, elemental composition, trophic position, consumption rate, and bioturbation) traits. Because intraspecific variability plays a crucial role in community dynamics and can promote species coexistence through niche partitions, we expected significant trait differences between the two species [START_REF] Shea | Community ecology theory as a framework for biological invasions[END_REF][START_REF] Jackson | Divergence in the trophic niche of sympatric freshwater invaders[END_REF]. Moreover, we expected P.

clarkii to have greater impacts on ecosystem functioning because other studies reported that F. limosus can be disadvantaged when co-occurring with other crayfish invaders in terms of access to shelter and trophic resources (Hudina et al., 2011). Second, we quantified the covariations in response and effect traits within each species (i.e. response and effect syndromes) and we evaluated how they covaried together to impact the ecosystem functioning (i.e. functional syndrome; Raffard et al., 2017;[START_REF] Diaz Pauli | Ecosystem consequences of multi-trait response to environmental changes in Japanese medaka, Oryzias latipes[END_REF]. We predicted that coexisting P. clarkii and F. limosus would display contrasting structure of trait variations and covariations (i.e. different functional syndromes; Raffard et al., 2017) due to their intrinsic biological differences (developmental pathways and genetic influence), hence entailing distinct specific impacts on ecosystem functioning [START_REF] Clark | High-dimensional coexistence based on individual variation: a synthesis of evidence[END_REF].

Material & methods

Model species

Native from Northern America, the invasive spiny-cheek crayfish F. limosus, was deliberately first introduced into Poland in 1890 and spread successfully across Europe [START_REF] Filipová | Haplotype variation in the spinycheek crayfish Orconectes limosus: colonization of Europe and genetic diversity of native stocks[END_REF]. As a vector of the crayfish plague (Aphanomyces astaci), F. limosus highly contributed to decimate indigenous crayfish populations (Filipová et al., 2013). The red-swamp crayfish of P. clarkii is a worldwide invasive species originated from north-eastern Mexico and southcentral USA [START_REF] Gherardi | Crayfish invading Europe: the case study of Procambarus clarkii[END_REF][START_REF] Oficialdegui | Unravelling the global invasion routes of a worldwide invader, the red swamp crayfish (Procambarus clarkii)[END_REF]. P. clarkii was introduced into Spain in the 1970s for aquaculture purpose and, from there, the species has successfully colonized many countries in Europe. The first recording of P. clarkii in the sampling area (i.e.

southwestern France) dates back to 1995 [START_REF] Changeux | Évolution de la répartition des écrevisses en France Métropolitaine selon les enquêtes nationales mensées par le conseil supérieur de la pêche de 1977 à 2001[END_REF]. Procambarus clarkii and F.

limosus have been widely reported to induce various negative impacts resulting in a general loss of biodiversity in aquatic ecosystems [START_REF] Gherardi | Understanding the impact of invasive crayfish[END_REF][START_REF] Twardochleb | A global meta-analysis of the ecological impacts of nonnative crayfish[END_REF][START_REF] Souty-Grosset | The red swamp crayfish Procambarus clarkii in Europe: impacts on aquatic ecosystems and human well-being[END_REF]. Both species have an opportunistic omnivorous diet, with a preference for aquatic vegetation, decomposing organic matter and detritus, and therefore, can alter aquatic food webs at multiple levels (Pavlović et al., 2006;[START_REF] Twardochleb | A global meta-analysis of the ecological impacts of nonnative crayfish[END_REF]Jackson et al., 2014;[START_REF] Vojkovská | The diet of the spiny-cheek crayfish Orconectes limosus in the Czech Republic[END_REF]. P. clarkii and F. limosus are both known as bioturbators [START_REF] Statzner | Crayfish as geomorphic agents and ecosystem engineers: biological behavior affects sand and gravel erosion in experimental streams[END_REF][START_REF] Gherardi | Understanding the impact of invasive crayfish[END_REF]. Particularly, P. clarkii highly damages river and lake bank and depletes water quality with its burrowing behavior [START_REF] Correia | Burrowing behavior of the introduced red swamp crayfish Procambarus clarkii (Decapoda: Cambaridae) in Portugal[END_REF][START_REF] Gherardi | Understanding the impact of invasive crayfish[END_REF]. Both P. clarkii and F. limosus display high aggressiveness and competitiveness [START_REF] Gherardi | Agonism and interference competition in freshwater decapods[END_REF]Buřič, 2009), as well as a high level of plasticity [START_REF] Gherardi | Crayfish invading Europe: the case study of Procambarus clarkii[END_REF], which can explain their invasive potential.

Despite these similarities, the two species display contrasted behavior: numerous studies suggest that F. limosus is disadvantaged in terms of shelter competition (Maiwald et al., 2006;[START_REF] Chucholl | Aggressive interactions and competition for shelter between a recently introduced and an established invasive crayfish: Orconectes immunis vs. O. limosus[END_REF], and aggressiveness [START_REF] Chucholl | Aggressive interactions and competition for shelter between a recently introduced and an established invasive crayfish: Orconectes immunis vs. O. limosus[END_REF]Hudina & Hock, 2012;[START_REF] Gherardi | Climate warming and the agonistic behaviour of invasive crayfishes in Europe[END_REF] compared to P. clarkii, and differs in defence posture (claws opened and raised for P. clarkii and crossed locked claws in a "spinous ball" for F. limosus ;[START_REF] Holdich | The spiny-cheek crayfish, Orconectes limosus (Rafinesque, 1817) [Crustacea: Decapoda: Cambaridae], digs into the UK[END_REF]. Furthermore, F. limosus has already been reported as disadvantaged when co-occurring with other crayfish invaders, which suggests that P. clarkii would be favored in co-occurring populations, and could have greater implications on ecosystem functioning than F. limosus (Hudina et al., 2011).

Experimental design

In June 2018, 64 sympatric P. clarkii (carapace length range: 41.86 -62.97 mm) and 64

F. limosus (carapace length range: 28.58 -46.91 mm) individuals were collected on two occasions (14 th and 29 th June) from lake Lamartine, southwestern France (43°30'21.5" N, 1°20'32.7" E, max depth = 2.80 m, surface area = 3.85 ha). In this lake, P. clarkii and F. limosus have synchronized seasonal activity, which strengthens local interspecific competition throughout the year (Figure VI.S1). Individuals were sampled using 36 pairs of baited traps (one cylindrical trap: 62cm x 34cm x 34cm, mesh size: 10 mm; one rectangular trap: 95cm x 20cm x 20cm, mesh size: 4 mm) placed for one night along transect lines, so that the sampling encompassed the whole habitat variability, considering that phenotypic variability can be high across littoral and pelagic habitats in lakes [START_REF] Lang | Stable resource polymorphism along the benthic littoral-pelagic axis in an invasive crayfish[END_REF]. In laboratory, crayfish were individually sexed, weighed, measured for carapace length (± 0.01 mm), before being individually maintained in 50 l tanks, filled with 35L of dechlorinated water, and containing a bubble system. A pipe was provided as shelter only after the measurement of the first functional trait (i.e. voracity), to allow a visual inspection of crayfish. All individuals were under the same control photoperiod (9:15) and temperature (mean air temperature = 22.65 °C ± 0.21 SE, measured daily). The experiment was divided in two rounds with each round lasting 13 days. The exact same equipment and protocols were used in each round. Prior to trait measurements, individuals were acclimatized for 72h in the laboratory conditions. No trait measurement was done on one P. clarkii individual and one F. limosus individual which passed out during the first round passed, so measurements were performed on 63 individuals for each species. In fine, data were complete for 58 and 61 individuals for round 1 and round 2, respectively, due to mortality and/or technical issues during the experiment. More specifically, 33 P. clarkii (18 females and 15 males) and 25 F. limosus individuals (14 females and 11 males) were analysed during round 1, and 27 P. clarkii (14 females and 13 males) and 34 F. limosus individuals (14 females and 20 males) were used for the analysis. Sex ratio did not differ between species and round in our experimental design (χ 2 = 0.032, df = 1, p-value = 0.86).

Functional response trait measurements

Morphology

Body morphology was assessed using a combination of linear traits measured to the nearest 0.01 mm with a digital caliper (body height/ carapace length, chela height/body height; [START_REF] Larson | The signal crayfish is not a single species: cryptic diversity and invasions in the Pacific Northwest range of Pacifastacus leniusculus[END_REF] and geometric morphometrics [START_REF] Zelditch | Geometric morphometrics for biologists : a primer[END_REF]. To avoid any bias in morphological analyses, individuals were measured and pictured before any other sampling just after they have been euthanized. Nineteen landmarks were placed on crayfish bodies including cephalothorax and abdomen, and body shape variations were analysed using TpsDig2 v.2.17 [START_REF] Rohlf | The tps series of software[END_REF] and Morpho J v.1.06d [START_REF] Klingenberg | MORPHO J: an integrated software package for geometric morphometrics[END_REF], after the removal of allometry effect on body shape variation, using a regression of the Procrustes coordinates against log10-transformed centroid sizes, following Evangelista et al. (2019) and [START_REF] Lang | Stable resource polymorphism along the benthic littoral-pelagic axis in an invasive crayfish[END_REF]. A principal component analysis (PCA) implemented in Morpho J was performed on the regression residuals. The first axis explained 68.5% of the total variance and corresponded to the variability between species (Figure VI.S2). The scores on the second axis (PC2 morphoscores, which explained 10,2% of the total variance) corresponded to within species variability and were used in subsequent analyses to characterize each individual regardless of its species (i.e. without maximizing the effect of the species in further analyses).

Increasing values on the second axis were associated with shorter rostrum and larger cephalothorax (Appendix 2).

To synthetize body morphology, a PCA was performed on "PC2 morphoscores", "body height/ carapace length ratio" and "chela height/body height ratio". Body morphology score was computed as the score on the first PCA axis, which explained 62.2% of the variance.

Increasing values on the first axis were associated with increasing "PC2 morphoscores" (i.e.

shorter and wider cephalothorax and rostrum) and increasing "chela height/body height" (i.e.

Growth rate

We estimated the specific growth rates (SGR, % d -1 ) as:

!"# = ln(Xf) -ln (Xi) . × 100
where Xf and Xi were the final and initial body mass, and the initial and final carapace length, respectively, and T the time between the two measurements (13 days). Growth rate was computed as the score on the first PCA axis based on body weight growth rate and carapace length growth rate, which explained 84.4% of the variance. Increasing values on the first axis were associated with increasing growth rates (Figure VI.S3).

Behavior

Activity level was assessed using rectangular opaque containers (67,5 cm x 39 cm) filled with dechlorinated tap water. Individuals were put individually in stall buckets for 10 minutes and then acclimated for 10 minutes in the tanks, before being filmed for 10 minutes. The video was then analysed using LoliTrack software v.4 (Loligo®Systems) to get the active percentage (i.e. time proportion during which the individual is moving) of each individual (Raffard et al., 2017). Anxiety-like behavior was quantified by analysing video by eye during 10 extra minutes, as the proportion of time spent in dark zones created by the addition of a completely opaque lid on the half surface of the tank, at the end of activity measurement [START_REF] Fossat | Anxiety-like behavior in crayfish is controlled by serotonin[END_REF]. Behavioral was estimated as the "behavioral score" on the first PCA axis synthetizing activity and anxiety-like behavior, which explained 59.7% of the variance.

Increasing values on the first axis were associated with increasing activity and anxiety-like behavior levels (Figure VI.S3).

Metabolism

Individuals were inserted in airtight container connected to a closed circuit with circulating water and a measurement cell with a dioxygen sensor (optical probe WTW FDO®925 IDS and respirometer Multi 3620 IDS SET G WTW). The whole system was completely immerged in 50 L black and opaque tanks filled with dechlorinated water. Following 5 minutes of acclimation, dissolved dioxygen content was recorded every 30 seconds, during 20 minutes.

Metabolism of individuals was estimated using their dioxygen consumption rate as a proxy [START_REF] Brown | Toward a metabolic theory of ecology[END_REF], which was calculated as the slope opposite of the linear regression of the dissolved oxygen (mg.L -1 ) divided by crayfish body mass to get the metabolism per gram of crayfish.

Functional effect trait measurements

Excretion

Two hours prior to excretion measurement, crayfish were fed ad libitum. Nitrogen and phosphorus excretion were quantified by placing crayfish individually in plastic bags containing 500mL of mineral water, and measuring dissolved ammonium NH4 + and dissolved phosphate PO4 3-after 2 hours, once individuals were removed and taken back to their own tank. We filtered 100mL of water through a glass microfiber filter (Whatman, GF/C, diameter 1⁄4 25 mm) and samples were frozen at -20°C. Excretion rates (NH4 + , PO4 3-, mg l -1 h -1 ) were assessed using a high-performance ionic chromatograph (Dionex DX-120), following Raffard et al. (2017) and were corrected for crayfish body mass (g). We performed a PCA on NH4 + and

Stoichiometry

At the end of the experiment, after other trait measurements, crayfish were frozen and stocked at the laboratory at -20°C to be subsequently lyophilized (Christ Alpha 1-4 LDPLUS).

Individuals were then ground to powder with two successive grinders (Waring WSG30E, Retsch MM200) and Carbon and Nitrogen contents were measured using an elementary analyser (Flash 2000 Thermofisher). Sampled were mineralized by sodium persulfate oxidation at 121°C for 2 hours, and mineral phosphorus contents were obtained using spectrophotometric analyses, by reacting with ammonium molybdate (AFNOR 1990). C:N, C:P and N:P molar ratios were then computed using the molar masses of the three elements.

For elemental composition, we used the score on the first PCA axis as "stoichiometric score", synthetizing C:N:P molar ratios (explained variance = 79.3%). Increasing values on the first axis were associated with increasing C:N ratio and decreasing C:P and N:P ratios (Figure

VI.S3

).

Trophic position

Trophic position of individuals was estimated using stable isotope analyses. To this end, a sample of abdominal muscle was collected on each individual after they have been euthanized and photographed. The tissue sample was subsequently rinsed with distilled water, oven dried at 60°C for 48h, ground to a fine powder, and analysed for nitrogen (δ 15 N) stable isotopes at the Cornell Isotope Laboratory (COIL, New York).

Consumption rate

Voracity was quantified by introducing 30 freshly defrosted red maggots in individual tanks.

We assessed the number of remaining pinkies after 15 minutes. Voracity was estimated as the number of red maggots consumed by gram of crayfish per minute.

Then, we quantified leaf consumption rate by introducing 4.0g of Populus nigra leaves in their home tank. In order to allow bacterial colonization and to improve appetence and digestibility of litter by crayfish, leaves were submerged in thin mesh bags (0.5mm; to prevent decomposition by invertebrates) for 10 days in water collected in the Canal du Midi (43° 33' 36.194'' N,1° 28' 31.967'' E). Leaves were left for 72h in individuals' tanks, following Raffard et al. (2017). After the 72h, the remaining leaf litter was removed, rinsed carefully on a sieve (250µm mesh-size) and then oven-dried for 72h at 70°C, before being weighed twice at the nearest 0.01mg. The weight of remaining leaf litter was computed at the average of these two values. before We estimated the leaf consumption rate as the weight of leaves consumed per day per gram of crayfish. The "consumption rate" was computed as the score on the first PCA summarizing voracity and litter consumption rate (explained variance = 66.1%).

Increasing values on the first axis were associated with increasing litter consumption and increasing voracity (Figure VI.S3).

Bioturbation

Bioturbation was measured as a consequence of burrowing by placing crayfish individually in buckets containing 3l of dechlorinated water and a roll of natural white clay (diameter 3.4 cm; length 3.9 cm; weight = 179 g) for 30 minutes. We used a portable turbidimeter (EUTECH TN-100 IR) to measure the turbidity (± 0.01 NTU) at tinitial = 0, and tfinal = 30 minutes. The bioturbation was calculated as the difference between final and initial turbidity and was divided by crayfish body mass to get the bioturbation per gram of crayfish.

Statistical analyses

Quantification of intraspecific variability and species comparison

In the subsequent analyses we used 5 response traits (body morphology, chela strength, growth rate, behavior, and metabolism) and 5 effect traits (excretion, elemental composition, trophic position, consumption rate and bioturbation) to characterize P. clarkii (n = 60) and F. limosus (n = 59).

To test if each response and effect trait differed between species and sexes, linear mixed models (LMMs) were run on each response and effect traits, using "sex" and "species" as fixed effects and "round" as random factor. Interactions were removed when non-significant.

Type II "Anova" implemented in the "car" package (v.3.0.5; [START_REF] Fox | An R companion to applied regression[END_REF]) was used to test the significance of each factor.

It is interesting to note that body morphology, chela strength and elemental composition differed significantly between sexes (Table VI.1; Figure VI.1). However, as the type of sexual dimorphism was similar in both species, the sex factor was not included in the following analyses.

Response and effect syndromes

For each species, correlations among response traits and among effect traits, respectively, were assessed using Spearman ranks correlations. Prior to further analyses, missing values were replaced using multivariate imputation with chain equations, using the R-package mice [START_REF] Azur | Multiple imputation bychained equations: what is it and how does it work[END_REF][START_REF] Van Buuren | mice: multivariate imputation by chained equations in R[END_REF]. Then, we assessed whether response and effect syndrome (i.e. covariance matrix of response and effect traits, respectively) differed between P. clarkii (n = 63) and F. limosus (n = 63) using structural equation modelling (SEM) and run models with covariations between all pairs of traits. First, we fitted a null model where all covariances were constrained to be equal between the two species (i.e. no differences of trait covariation between species). Second, we fitted an alternative model in which all covariances were unconstrained between the two species (i.e.

trait covariations differed between species). Finally, the models were compared using AIC and likelihood ratio test to assess whether the covariance matrices were globally different (i.e.

alternative model with the lowest AIC) or not (i.e. null model with the lowest AIC) between P.

clarkii and F. limosus [START_REF] Raffard | Does range expansion modify trait covariation? A study of a northward expanding dragonfly[END_REF]. This procedure was performed for response and effects traits separately. SEM were run using the R-package lavaan [START_REF] Rosseel | lavaan: an R package for structural equation modeling[END_REF].

Functional syndromes

To assess the potential consequences of response traits on ecosystem functioning in the two species, the link between response and effect traits was tested using partial least-squares path modelling (Sanchez, 2013). Traits were first scaled to the mean within each species to facilitate comparison. We constructed models with response and effect traits summarized in latent variables representing response and effect syndromes, and a directional path was fitted between the response syndrome and the effect syndrome (Raffard et al., 2017). The significance of the path from response syndrome to effect syndrome, and the contribution (i.e. loadings) of each trait in the syndrome (i.e. latent variables) were estimated using 95% confidence intervals (CIs) based on 1000 bootstraps. We performed one model for each species, and loadings on latent variables and the link from response syndrome to effect syndrome were compared using 95% CIs. PLS-PM was run using the R-package plspm (Sanchez, 2013).

Results

Interspecific differences

Response traits

Overall, we found that body morphology, behavior and metabolism differed significantly between these two species (LMM,F1,115.82 = 116.18 . clarkii, respectively). Metabolic rate also differed between the two species: F. limosus individuals consumed more dioxygen than P. clarkii individuals (mean ± SE = 3.11 ± 0.16 g(O2).

L -1 .h -1 .g -1 and mean ± SE = 1.73 ± 0.08 mg(O2). L -1 .h -1 .g -1 for F. limosus and P. clarkii, respectively; Figure

Effect traits

Elemental composition, excretion and trophic position differed significantly between the two species (LMM,F1,115.45 = 95.71,P < 0.001;F1,115.74 = 82.54,P < 0.001;F1,115.76 = 23.43

Response and effect syndromes

Regarding response syndromes, behavior was significantly and positively correlated with metabolism in P. clarkii (ρ = 0.43, P < 0.001; Table VI.2) and negatively correlated with growth rate in F. limosus (ρ = -0.35, P = 0.007; Table VI.2). All other correlations among response traits were non-significant (Table VI.2). Regarding effect syndromes, elemental composition was significantly and negatively correlated with excretion and consumption rates, and bioturbation in P. clarkii (ρ = -0.38, P = 0.003; ρ = -0.58, P < 0.001; ρ = -0.51, P < 0.001;

Table VI.3). Excretion and consumption rates, and bioturbation were all positively correlated among each other (ρ excretion -consumption = -0.54, P < 0.001; ρ excretion -bioturbation = 0.33, P = 0.010; ρ consumption -bioturbation = 0.44, P < 0.001; Table VI.3). Trophic position was also significantly and positively correlated with excretion rate in P. clarkii (ρ = 0.26, P = 0.046), but was not correlated with any other traits (Table VI.3). In F. limosus, there was a unique significant and negative correlation between trophic position and body stoichiometry (ρ = -0.34, P = 0.008;

Discussion

To our knowledge, this is the first study focusing on functional syndromes of co-existing invasive species. Our study demonstrated a high difference in functional traits, trait covariations, and functional syndromes between two co-occurring invasive crayfish species.

First, we highlighted a high level of trait variability among individuals between P. clarkii and F. limosus. We also demonstrated a significant difference of response and effect trait covariations between crayfish species. Finally, we demonstrated that this heterogenous structure of trait covariations resulted in different functional syndromes. This high level of intraspecific variability, which often characterizes invasive species, is crucial to respond to changing environmental conditions [START_REF] Messager | Phenotypic variability of rusty crayfish (Faxonius rusticus) at the leading edge of its riverine invasion[END_REF]. Our results suggest that cooccurring invasive crayfish species could develop differentiated strategies that entail contrasting impacts on ecosystem functioning.

Response traits and covariations

F. limosus and P. clarkii had contrasting response and effect traits and syndromes (i.e.

heterogenous intensities and direction of covariations), suggesting that they do not respond equally to the same environmental conditions. The coexistence of these two ecologically close crayfish species might be favored by their differentiation due to their respective high intraspecific variations (leading to niche partitions; [START_REF] Courbaud | Intra-specific variability and the competition-colonisation trade-off: coexistence, abundance and stability patterns[END_REF][START_REF] Wong | Trait-based ecology of terrestrial arthropods[END_REF].

Globally, F. limosus individuals had a stockier cephalothorax, larger chelae et more elongated abdomen than P. clarkii. Despite a significant difference in chelae morphology, the species did not differ in chelae strength, suggesting that F. limosus and P. clarkii had the same advantage in foraging, defense against predators, and reproductive success (Hudina et al., 2012). F. limosus also displayed a higher level of locomotor activity than P. clarkii and a higher metabolism, but there was no pronounced difference in anxiety-like behaviour between species which could suggest a mismatch during competitive encounters between the two species with an advantage for P. clarkii. Surprisingly, anxiety-like behaviour and activity were positively correlated suggesting that activity had reflected a stress level of crayfish in our study. This goes against the POLS concept [START_REF] Reale | Personality and the emergence of the pace-of-life syndrome concept at the population level[END_REF] and previous studies on crayfish behavior that have highlighted a positive correlation between boldness (i.e. opposite to anxiety-like behavior), activity and aggressiveness [START_REF] Pintor | Differences in aggression, activity and boldness between native and introduced populations of an invasive crayfish[END_REF][START_REF] Pintor | Behavioral correlations provide a mechanism for explaining high invader densities and increased impacts on native prey[END_REF][START_REF] Linzmaier | Towards a mechanistic understanding of individuallevel functional responses: invasive crayfish as model organisms[END_REF]. For both species, response traits were poorly correlated, and response syndrome involved the behavior of individuals. Concerning P. clarkii, the more active and anxious individuals had the higher metabolism and in F. limosus, the more active and anxious individuals had slower growth rate, indicating that P. clarkii seemed to have a faster pace of life than its sympatric heterospecific congeners [START_REF] Reale | Personality and the emergence of the pace-of-life syndrome concept at the population level[END_REF]. It has been demonstrated

that behavior can be associated with dispersal rate in invasive species [START_REF] Fraser | Explaining leptokurtic movement distributions: intrapopulation variation in boldness and exploration[END_REF][START_REF] Duckworth | Coupling of dispersal and aggression facilitates the rapid range expansion of a passerine bird[END_REF]. Here, our results illustrated the importance of behavior in response trait covariations and in functional syndromes of invasive species which could lead to contrasting impacts of invaders on native prey communities [START_REF] Pintor | Behavioral correlations provide a mechanism for explaining high invader densities and increased impacts on native prey[END_REF]. Individuals, through different behavior, face various selection pressures that lead to a high variability in morphological or physiological traits (e.g. metabolism) which can result in differential impacts on ecosystem functioning [START_REF] Duckworth | The role of behavior in evolution: a search for mechanism[END_REF][START_REF] Rota | Phenotypic determinants of interindividual variability of litter consumption rate in a detritivore population[END_REF].

Effect traits and covariations

Concerning effect traits, the consumption rate and the bioturbation due to the burrowing activity of F. limosus and P. clarkii did not differ, indicating that these traits cannot be the factors of differentiated nutrients bioavailability or recycling between these species in the ecosystem. However, F. limosus displayed a higher trophic position than P. clarkii while both crayfish species are omnivorous with a preference for detritus and vegetation. Hence, our results indicated that the diet of P. clarkii involved a higher proportion of plants and detritus, and suggested that F. limosus is disadvantaged in food acquisition in the study system and consumes more preys of higher trophic levels (e.g. macroinvertebrates, fish eggs or larvae).

F. limosus also excreted more NH4 + and PO4 3-than P. clarkii, and displayed lower C:N and higher N:P and C:P ratios) than P. clarkii. Phosphorous is essential for individual growth and has already been shown to be the most important source of stoichiometric variations for crayfish, while the two major molecules (proteins and nucleic acids) vary little in terms of C and N contents [START_REF] Sterner | Ecological stoichiometry: The biology of elements from molecules to the biosphere[END_REF][START_REF] Faerøvig | Allocation strategies in crustacean stoichiometry: the potential role of phosphorus in the limitation of reproduction[END_REF]. Higher N:P ratios in F.

limosus suggested that the allocation in chitin in spiny-cheek crayfish is more important, providing a stronger carapace as defence against predators compared to P. clarkii [START_REF] Elser | Organism size, life history, and N:P stoichiometry[END_REF]. Lower C:P and N:P ratios in P. clarkii (i.e. higher %P) could be the result of an increased allocation in growth rate, or greater storage of P in the organism's tissues, suggesting that P. clarkii had a rapid growth rate (i.e. predation defence through gape limitation) or would have a better tolerance to P limitation, compared to F. limosus. Hence, we suggest that differences of elemental composition are key to contrasting effects of P.

clarkii and F. limosus on microbial respiration rates, producers dynamics and nutrients cycling in the environment due to different intake and contrasting excretion rates [START_REF] Yamamichi | Rapid evolution of a consumer stoichiometric trait destabilizes consumer-producer dynamics[END_REF][START_REF] Vanni | Predicting nutrient excretion of aquatic animals with metabolic ecology and ecological stoichiometry: a global synthesis[END_REF][START_REF] Welti | Bridging food webs, ecosystem metabolism, and biogeochemistry using ecological stoichiometry theory[END_REF], and dissimilar bottom-up consequences in the food web [START_REF] Malzahn | Nutrient limitation of primary affects fish condition producers planktivorous[END_REF].

P. clarkii individuals with higher N:P and C:P ratios and lower C:N ratios had lower levels of NH4 + and PO4 3-excretion, and lower consumption rate and bioturbation. This suggested that P. clarkii can better retain N and P in their tissues compared to F. limosus (i.e. better resistance to P limitations), and that they are globally more efficient in nutrients acquisition (i.e. less bioturbation maybe due to reduced foraging activity, as individuals with higher consumption rates make higher level of bioturbation). As expected, individuals with greater consumption rates had greater excretion rates. For both species, the effect syndrome involved trait correlations with the stoichiometry, suggesting that effects of individuals directly depend on their physiological characteristics (here, stoichiometric traits), and supporting the idea that stoichiometric traits should be considered as functional traits (e.g. C:N:P ratios and proportions, Leal et al., 2017b), to fully appreciate their intrinsic role in consumer-driven nutrient recycling and eco-evolutionary dynamics [START_REF] Matthews | Toward an integration of evolutionary biology and ecosystem science[END_REF][START_REF] Hawlena | Fear of predation slows plant-litter decomposition[END_REF][START_REF] Welti | Bridging food webs, ecosystem metabolism, and biogeochemistry using ecological stoichiometry theory[END_REF]. Effect traits were more strongly correlated in P. clarkii, suggesting that this invasive species might have more predictable impacts on ecosystem functioning compared to F. limosus.

Functional syndromes

In P. clarkii the response syndrome correlated with anxiety-like behavior and activity, while in F. limosus it was positively associated with growth rate. In both species, the metabolism was correlated with the response syndrome, which confirms that variations in metabolism could drive covariations between response and effect traits, as previously suggested [START_REF] Biro | Do consistent individual differences in metabolic rate promote consistent individual differences in behavior?[END_REF][START_REF] Reale | Personality and the emergence of the pace-of-life syndrome concept at the population level[END_REF]Raffard et al., 2017). Our results are in line with the metabolic theory of ecology which states that the metabolism of organisms drive ecological processes through different levels of biological organization [START_REF] Brown | Toward a metabolic theory of ecology[END_REF]. Metabolism is a key trait that results from a fitness trade-off of individuals and constrains their contribution to biogeochemical processes through trophic fluxes, respiration and nutrients excretion [START_REF] Vanni | Predicting nutrient excretion of aquatic animals with metabolic ecology and ecological stoichiometry: a global synthesis[END_REF].

The effect syndrome in P. clarkii was based on a suite of effect traits (stoichiometry, excretion and consumption rates and bioturbation), while it was only associated with bioturbation in F.

limosus. The functional syndromes of these two invasive crayfish species highlight their ability to physically modify their environment, as biological engineers. Their burrowing activity is functionally important because it impacts the physical structure of habitat (e.g. water turbidity, reduced benthic vegetation), and the bioavailability of nutrients in the ecosystem [START_REF] Statzner | Crayfish as geomorphic agents and ecosystem engineers: biological behavior affects sand and gravel erosion in experimental streams[END_REF][START_REF] Twardochleb | A global meta-analysis of the ecological impacts of nonnative crayfish[END_REF]. The numerous trait covariations in P. clarkii' functional syndrome suggested that the variation of response traits in this species would result in high intensity effects and/or a high range of effects on ecosystem functioning, compared to F. limosus.

Our study demonstrated that, in each species, the response syndrome was associated with the effect syndrome, resulting in a functional syndrome. This indicated that variations in response traits and response trait covariations in each species could result in differentiated impacts on ecosystem functioning. Raffard et al. (2019[START_REF] Raffard | Does range expansion modify trait covariation? A study of a northward expanding dragonfly[END_REF] demonstrated that covariations among functional traits are population-specific. Our study provides the evidence that ecologically close species that co-occur can display contrasting functional syndromes. This can be facilitated by the necessity for P. clarkii and F. limosus to use different life-history strategies to reduce the overlap of ecological niches, therefore, allowing their coexistence [START_REF] Wong | Trait-based ecology of terrestrial arthropods[END_REF]. [START_REF] Závorka | Co-existence with non-native brook trout breaks down the integration of phenotypic traits in brown trout parr[END_REF] demonstrated that coexistence of an invader and a native species can lead to the breakdown of trait covariations in the native species which is outcompeted, reducing its fitness. As we predicted based on previous studies, P. clarkii seems to be more competitive than F. limosus which displayed a weaker functional syndrome.

Indeed, this suggested that P. clarkii individuals had a greater adaptive capacity by changing their phenotype in a consistent way thanks to trait intercorrelations. It could be interesting to compare the functional syndromes of coexisting populations and allopatric populations (close to our study site (Lang et al. in prep)) within both invasive species to assess if trait covariations are stronger when they are allopatric and if coexistence does affect their traits (through competition, predation pressure or indirectly; [START_REF] Závorka | Co-existence with non-native brook trout breaks down the integration of phenotypic traits in brown trout parr[END_REF].

Conclusion

To conclude, we demonstrated that co-occurring invasive crayfish species displayed contrasting functional syndrome. Our study supports that stoichiometric traits and metabolism play a pivotal role in the functional syndrome. In the context of biological invasions, quantifying trait covariations can help to fully apprehend invasive individuals' intrinsic functional strategies. Plus, it offers a better comprehension and prevision of invasive species impacts by linking response trait measurements to ecosystem processes without measuring effect traits, which can be challenging in natural populations. This could also help predicting the potential shifts of trait covariations due to invasive species management, and the resulting effects on ecosystem functioning, that could be unexpectedly counterproductive otherwise. However, our study highlighted that these predictions can be intricate depending on the considered species in a context of multi-invasions. [START_REF] Parsons | Getting into shape: an empirical comparison of traditional truss-based morphometric methods with a newer geometric method applied to New World cichlids[END_REF][START_REF] Zelditch | Geometric morphometrics for biologists : a primer[END_REF]. D'autres travaux avaient déjà mis en évidence une très grande variabilité de morphologie chez les deux espèces, soulignant la nécessité de considérer la variabilité intraspécifique à une échelle géographique fine [START_REF] Chybowski | Morphometrics, fecundity, density, and feeding intensity of the spinycheek crayfish, Orconectes limosus (Raf.) in natural conditions[END_REF]Evangelista et al., 2019a). Cette forte variabilité morphologique suggère que chaque espèce invasive possède une grande diversité d'impacts sur les processus écosystémiques des lacs de gravière étudiés que ce soit au sein ou entre populations (Chapitres IV, V; Evangelista et al., 2019b). Des études récentes ont démontré que les traits physiologiques ou comportementaux pouvaient être de meilleurs prédicteurs des effets des individus sur le fonctionnement de l'écosystème que les traits morphologiques (Raffard et al., 2017;[START_REF] Rota | Phenotypic determinants of interindividual variability of litter consumption rate in a detritivore population[END_REF]

Coexistence d'espèces invasives et conséquences sur le fonctionnement de l'écosystème

Plusieurs résultats dans ce travail de thèse suggèrent que, même si P. clarkii et F. limosus ont des impacts importants sur le fonctionnement des écosystèmes, il semblerait que (i) P. clarkii soit plus compétitrice que F. limosus dans les sites étudiés, et (ii) la nature et l'intensité des impacts diffèrent entre les deux espèces. Ces deux constats résultent de plusieurs observations. Premièrement, la variabilité génétique de P. clarkii est beaucoup plus importante que celle de F. limosus (Chapitre III), ce qui lui confère un avantage pour assurer le maintien de ses populations [START_REF] Frankham | Introduction to conservation genetics[END_REF]. Il faut cependant noter que F. limosus a l'avantage non négligeable d'être capable de parthénogenèse, du moins en milieu contrôlé [START_REF] Buřič | A successful crayfish invader is capable of facultative parthenogenesis: a novel reproductive mode in decapod crustaceans[END_REF], ce qui pourrait expliquer le maintien de ses populations naturelles malgré une faible variabilité génétique. Ensuite, nous avons observé que les densités de population sont souvent beaucoup plus importantes chez P. clarkii à la fois dans les populations sympatriques et allopatriques ce qui suggère que l'espèce est plus compétitrice que F. limosus (Chapitres IV, V ; e.g. stratégie r plus marquée pour P. clarkii). Enfin, le faible syndrome fonctionnel de F. limosus suggère que les impacts de l'espèce sont moins diversifiés et/ou de plus faible intensité que ceux de P. clarkii (Chapitre VI). De plus, cette faible structuration de covariation pourrait être due à la colonisation plus tardive du lac par P.

clarkii (lac creusé en 1987) qui, à son arrivée, aurait pu provoquer l'écroulement du syndrome fonctionnel de F. limosus [START_REF] Závorka | Co-existence with non-native brook trout breaks down the integration of phenotypic traits in brown trout parr[END_REF]. Nos résultats vont dans le sens d'autres études qui ont montré que P. clarkii était plus agressive, plus compétitrice (dans l'acquisition des ressources et l'accès au terrier) et plus tolérante aux stress environnementaux que F.

limosus [START_REF] Holdich | The spiny-cheek crayfish, Orconectes limosus (Rafinesque, 1817) [Crustacea: Decapoda: Cambaridae], digs into the UK[END_REF][START_REF] Capinha | Effects of climate change, invasive species, and disease on the distribution of native european crayfishes[END_REF][START_REF] Gherardi | Climate warming and the agonistic behaviour of invasive crayfishes in Europe[END_REF]. Enfin, des analyses préliminaires sur l'ensemble de nos données ont mis en évidence des différences de trait trophique chez F. limosus entre populations allopatriques et sympatriques, mais pas simuler les populations sympatriques. Les sex-ratios seraient équilibrés (1:1) dans chaque mésocosme afin de pallier aux potentiels effets de sex-ratio sur les dynamiques écosystémiques [START_REF] Fryxell | Sex ratio variation shapes the ecological effects of a globally introduced freshwater fish[END_REF]. Enfin, pour comparer l'effet de l'introduction d'écrevisses et l'effet du traitement (allopatrique ou sympatrique), il y aurait un traitement sans écrevisse. Chaque traitement serait répliqué 3 fois comme présenté sur la figure VII.2 : L'adaptation locale est un mécanisme pouvant mener à des divergences entre, et au sein même des populations à des échelles géographiques très restreintes [START_REF] Fraser | Extent and scale of local adaptation in salmonid fishes: review and meta-analysis[END_REF][START_REF] Weber | Fine-scale thermal adaptation in a green turtle nesting population[END_REF]. Elle est cruciale chez les espèces invasives puisqu'elle favorise leur capacité de dispersion, et nous avons montré qu'elle pouvait être très importante dans des populations récemment établies (Chapitres IV, V). Des études montrent qu'elle se développe en 6-30 générations [START_REF] Fraser | Extent and scale of local adaptation in salmonid fishes: review and meta-analysis[END_REF] Le changement global implique des variations temporelles dans les dynamiques écoévolutives [START_REF] Bailey | From genes to ecosystems: an emerging synthesis of eco-evolutionary dynamics[END_REF]. Par exemple, sous l'effet de l'anthropisation continuelle des milieux (e.g. urbanisation), les traits phénotypiques des organismes sont soumis à de fortes pressions environnementales et sont amenés à changer rapidement [START_REF] Alberti | Eco-evolutionary dynamics in an urbanizing planet[END_REF]. Les inconnues sont encore nombreuses concernant les réponses adaptatives des espèces au changement climatique, qui peuvent impliquer de multiples traits (e.g. plasticité des traits comportementaux, physiologiques, morphologiques) ainsi que des mécanismes génétiques et épigénétiques [START_REF] Catullo | The potential for rapid evolution under anthropogenic climate change[END_REF]. Intégrer l'évolution temporelle dans l'étude de la variabilité intraspécifique est essentiel pour tirer des leçons du passé et mieux prévoir le futur.

Ce type d'approche permettrait notamment d'étudier en synergie divers mécanismes agissant à différentes échelles de temps : par exemple cela aiderait à mieux comprendre les relations entre plasticité et adaptation (Hendry, 2016;Fox et al., 2019). Il serait également pertinent d'étudier la stabilité des structures de covariation de traits dans le temps. Des études prenant en compte la temporalité des variations phénotypiques permettent de mieux estimer notre capacité à restaurer des populations d'animaux sauvages, et notamment leur variabilité intraspécifique et leurs dynamiques éco-évolutives d'origine [START_REF] Thompson | Anthropogenic habitat alteration leads to rapid loss of adaptive variation and restoration potential in wild salmon populations[END_REF].

En conséquence de ces changements de variabilité génétique et phénotypique au cours du temps, les impacts des variations intraspécifiques sur les dynamiques éco-évolutives et le fonctionnement des écosystèmes sont susceptibles de varier dans le temps [START_REF] Crutsinger | Temporal dynamics in non-additive responses of arthropods to host-plant genotypic diversity[END_REF]. Les espèces invasives constituent un modèle d'étude pertinent pour étudier l'aspect temporel de la variabilité intraspécifique puisqu'elles ont des impacts fonctionnels importants et qu'au cours du processus d'invasion, les individus sont soumis très rapidement à une succession de pressions de sélection qui façonnent leurs patrons de variabilité intraspécifique [START_REF] Pyšek | Spatio-temporal dynamics of plant invasions: linking pattern to process[END_REF]. Il en résulte que les processus écologiques et évolutifs peuvent évoluer à des échelles de temps comparables [START_REF] Matthews | Toward an integration of evolutionary biology and ecosystem science[END_REF]Figure VII.3).

Un suivi des populations d'écrevisses permettrait d'évaluer l'évolution des parts respectives des processus neutres et adaptatifs (et les parts respectives de la sélection et de l'adaptation) au cours du temps dans les différentes populations. La variation temporelle des traits et donc de l'impact des organismes invasifs devrait être prise en compte par les gestionnaires qu'elle soit saisonnière ou, à une plus large échelle de temps, due à des variations climatiques ou à l'histoire de colonisation [START_REF] Parker | An evolutionary approach to understanding the biology of invasions: local adaptation and general-purpose genotypes in the weed Verbascum thapsus[END_REF]Phillips & Shine, 2006). [START_REF] Catton | Environmental sociology : a new paradigm[END_REF]. D'une manière générale, l'étude des invasions biologiques s'inscrit parfaitement dans ce champs disciplinaire puisque l'Homme est souvent à l'origine du déplacement des individus hors de leur aire de répartition naturelle et les espèces invasives peuvent en retour impacter les services écosystémiques, et donc les sociétés [START_REF] Simberloff | Impacts of biological invasions: what's what and the way forward[END_REF]. Bien que les changements culturels puissent être beaucoup plus fréquents et rapides que les variations de traits biologiques [START_REF] Catton | Environmental sociology : a new paradigm[END_REF], il est important de prendre en compte les facteurs anthropiques sous-jacents aux invasions biologiques dans le but de mieux les prédire (e.g. quelles motivations, quels vecteurs), mais aussi pour mieux comprendre leurs impacts sur le fonctionnement des écosystèmes (e.g. quels traits sont sélectionnés par l'Homme ; [START_REF] Jeschke | Determinants of vertebrate invasion success in Europe and North America[END_REF]. Nous l'avons évoqué en introduction, l'Homme peut également modifier les traits et donc les impacts des individus invasifs par les pratiques de gestion qu'il met en place (ou non) pour contrôler ou éradiquer les populations invasives (Annexe I), ou par le transport d'individus invasifs (volontaire ou accidentel) entre écosystèmes. Ces pratiques de gestion et déplacements d'individus invasifs sont susceptibles d'évoluer avec le contexte éco-sociologique selon la localisation de la population invasive, mais aussi au cours du temps à travers des perceptions changeantes de la part du grand public et des gestionnaires, ou encore des changements politiques [START_REF] Verbrugge | Exploring public perception of non-native species from a visions of nature perspective[END_REF][START_REF] Crowley | Conflict in invasive species management[END_REF][START_REF] Kochalski | Public perception of river fish biodiversity in four European countries[END_REF]. Dans le contexte de changement global, les impacts dus au changement climatique et aux activités humaines sur la variabilité intraspécifique sont souvent étudiés séparément. Une étude récente a mis en évidence la sélection synergique de la pêche et du changement climatique sur les traits phénotypiques des poissons marins [START_REF] Morrongiello | Fishing constrains phenotypic responses of marine fish to climate variability[END_REF]. Une compréhension plus fine des patrons de variabilité intraspécifique et des conséquences de cette variabilité sur le fonctionnement des écosystèmes nécessiterait plus d'études intégrant à la fois les déterminants environnementaux et anthropiques de la variabilité intraspécifique. Ce type d'approche est notamment pertinent pour l'étude la variabilité intraspécifique des espèces invasives.

Un cadre d'étude : le méta-socio-écosystème

Dans ce travail, nous avons donc considéré deux métapopulations d'espèces invasives [START_REF] Hanski | Metapopulation biology: ecology, genetics and evolution[END_REF]. Les lacs de gravière étudiés dans cette thèse constituent en effet une véritable une mosaïque d'îles aquatiques dans une matrice terrestre et forment un métaécosystème commun aux deux espèces [START_REF] Loreau | Meta-ecosystems: a theoretical framework for a spatial ecosystem ecology[END_REF]. Par définition, le métaécosystème implique l'existence de flux de matière, d'énergie et d'organismes entre les populations [START_REF] Loreau | Meta-ecosystems: a theoretical framework for a spatial ecosystem ecology[END_REF][START_REF] Gounand | Meta-ecosystems 2.0: rooting the theory into the field[END_REF]. Ces flux résultent de la nature même des gravières : les flux de minéraux sont rendus possibles entre lacs proches par la nappe souterraine commune [START_REF] Mollema | Water and (bio)chemical cycling in gravel pit lakes: a review and outlook[END_REF] ; les gravières constituent des habitats pour la faune aviaire qui participe à entretenir des flux entre les populations. Certaines études suggèrent que les oiseaux sont susceptibles de déplacer des individus invasifs [START_REF] Anastácio | Waterbirdmediated passive dispersal is a viable process for crayfish (Procambarus clarkii)[END_REF][START_REF] Lovas-Kiss | Experimental evidence of dispersal of invasive cyprinid eggs inside migratory waterfowl[END_REF]. Les écrevisses ont également la capacité de se déplacer entre sites proches par voie terrestre [START_REF] Puky | Invasive crayfish on land: Orconectes limosus (rafinesque, 1817) (decapoda: Cambaridae) crossed a terrestrial barrier to move from a side arm into the danube river at Szeremle, Hungary[END_REF][START_REF] Thomas | Terrestrial emigration behaviour of two invasive crayfish species[END_REF], mais une étude récente menée dans un méta-écosystème composé de mares pourtant très proches les unes des autres par rapport au site d'étude de cette thèse, a montré que ce type de déplacement est peu fréquent car très couteux [START_REF] Tréguier | Is it a hindrance for an invasive aquatic species to spread across scattered habitat patches ?[END_REF]. Dans le cas des lacs de gravière, il est probable que les flux soient principalement assurés par les flux anthropiques liés aux différentes activités qu'hébergent les lacs (Chapitre III ; [START_REF] Rahel | Unauthorized fish introductions: fisheries management of the people, for the people, or by the people[END_REF]. La nature et l'intensité de ces activités peuvent être elles-mêmes impactées par l'accessibilité des lacs par l'Homme [START_REF] Kaufman | Impacts of road access on lake trout (Salvelinus namaycush) populations: regional scale effects of overexploitation and the introduction of smallmouth bass (Micropterus dolomieu)[END_REF]. La notion de méta-écosystème ne prend pas en compte les relations que nous avons illustrées dans le précédent paragraphe, entre la société et son environnement. Dans le but de mieux prédire les futures invasions et d'appréhender plus finement les conséquences des espèces invasives, il serait intéressant de considérer le système comme un méta-socio-écosystème, cadre conceptuel proposé par [START_REF] Renaud | Towards a meta-social-ecological system perspective: a response to Gounand et al[END_REF]. Intégrer cet aspect social est pertinent surtout dans le contexte des invasions biologiques puisque les hommes en sont le principal vecteur. Cela peut se faire par l'intégration d'approches cognitives (i.e. modèles mentaux) pour mieux comprendre l'impact des effets culturels et de la perception des espèces invasives par les gestionnaires la variabilité intraspécifique de celles-ci à travers les pratiques de gestion, et in fine sur leur rôle des individus invasifs dans les processus écosystémiques. La désirabilité ou l'intérêt humain pourrait être considérés comme des traits à part entière pouvant expliquer le potentiel invasif des espèces non natives [START_REF] Marchetti | Invasive species profiling? Exploring the characteristics of non-native fishes across invasion stages in California[END_REF]. Il a été montré récemment que d'autres espèces invasives aquatiques (la perche-soleil Lepomis gibbosus et le poisson-chat Ameiurus melas) du même site d'étude présentaient des variations trophiques et morphologiques respectivement, dépendant des pratiques de gestion appliquées sur les différentes populations, validant l'utilisation du cadre conceptuel du méta-socio-écosystème [START_REF] Jorigné | Pratiques de gestion et consequences ećologiques sur des especes exotiques envahissantes dans des milieux aquatiques artificiels[END_REF].

Des approches combinant les facteurs sociaux et environnementaux (biotiques et abiotiques) permettraient donc d'améliorer notre connaissance des mécanismes façonnant la variabilité intraspécifique des espèces invasives, et donc leurs effets sur les dynamiques des communautés et le fonctionnement des écosystèmes [START_REF] Marr | Freshwater fish introductions in mediterranean-climate regions: are there commonalities in the conservation problem?[END_REF][START_REF] Clancy | Using social and physical variables to assess vulnerability of northwestern Montana lakes to illegal fish introductions[END_REF]Projet DISPERINVA). L'intérêt de telles approches intégratives réside également dans le développement et l'application de pratiques de gestion des espèces invasives adaptées [START_REF] Caplat | Integrating ecological knowledge, public perception and urgency of action into invasive species management[END_REF].

Annexes

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© The Ecological Society of America

Front Ecol Environ doi:10.1002/fee.1922 populations prior to harvest, the trait distributions of invaders might be limited as compared to the trait distributions of their native conspecifics (Juette et al. 2014), modifying the potential for harvesting to subsequently affect trait distribution. In addition, given the high costs of invasion control programs (Myers et al. 2000), invaders are often harvested at high intensity but over relatively short time periods. As a result, many invasion control programs are unsuccessful at permanently reducing or eradicating target populations (Britton et al. 2011; Pluess shooting and baiting, which reduced their activity at dusk and increased it at dawn, relaxing their top-down control of invasive feral cats Felis catus and increasing the likelihood of encounters between feral cats and native prey [START_REF] Brook | Effects of predator control on behaviour of an apex predator and indirect consequences for mesopredator suppression[END_REF]. There is also evidence to suggest that harvest-driven trait changes could affect ecosystem functioning. For example, in an experiment on the invasive red swamp crayfish (Procambarus clarkii), a modeling approach revealed that a substantial decrease in crayfish population size affected leaf-litter decomposition rate (a key ecosystem process) to a similar degree as did changes in crayfish behavioral, morphological, and life-history traits (Raffard et al. 2017). Harvest-driven trait changes might also modify the indirect effects of invasive species on recipient ecosystems. The removal of invasive pumpkinseed sunfish (Lepomis gibbosus) by angling leads to changes in sunfish population size distribution and size at maturity (Evangelista et al. 2015). As lifehistory traits affect fish diet composition [START_REF] Zandonà | Diet quality and prey selectivity correlate with life histories and predation regime in Trinidadian guppies[END_REF], these harvestmediated changes can then alter the nutrient-mediated effects of pumpkinseed sunfish on ecosystem processes (Evangelista et al. 2017).

The direction and magnitude of harvest-driven ecosystem effects might be expected to differ between native and invasive species. Although harvested native species usually have high economic, nutritional, and cultural values, these attributes are not necessarily linked to their ecosystem role. Conversely, invaders subjected to control methods are targeted due to their strong negative ecological impacts (Kopf et al. 2017) and are therefore likely to comprise a higher proportion of functionally important taxa (eg ecosystem engineers) than harvested native species. This leads us to predict that harvest-induced effects on invasive species should result more frequently in strong ecosystem responses. Moreover, invasion is a selective process where individuals pass through a sequence of filters that act on individual phenotypes to determine whether introduction, establishment, and spread are successful (Blackburn et al. 2011). Consequently, in Importance of harvest-driven trait changes for invasive species management Although intraspecific differences between the phenotypes of organisms are an important driver of ecological dynamics (Des [START_REF] Roches | The ecological importance of intraspecific variation[END_REF], research to help integrate phenotypic variation and its drivers with ecosystem management has been limited. For this reason, the novel conceptual framework proposed by Palkovacs et al. (2018) -which helps to clarify the ecological implications of harvest-driven trait changes -is timely.

Biological invasions are a key component of the current biodiversity crisis and affect all levels of biological organization. From local to global scales, efforts to control or eradicate invasive species aim to reduce the negative ecological and economic impacts associated with invaders (Kopf et al. 2017). Invasive species management commonly relies on methods including harvest (eg hunting and angling), as well as chemical and biological control measures, and can result in non-random removals of individuals from targeted populations (Myers et al. 2000;Britton et al. 2011). The potential selectivity of these methods therefore has strong ecological and evolutionary implications. Consequently, we suggest that [START_REF] Des Roches | The ecological importance of intraspecific variation[END_REF] framework could be applied to invasive species management. Indeed, harvest-driven trait changes in invasive species might induce unexpected and potentially counterproductive results that may not have been explicitly considered by ecosystem managers.

Recent studies have demonstrated how harvest modifies the traits of invaders and how these changes could modulate their ecological impacts (Figure 1). In populations of invasive lionfish (Pterois volitans) controlled by spearfishing, individuals have shifted their behavior to become more crepuscular, potentially increasing their encounter rates with native reef fishes at dawn and dusk (Côté et al. 2014). Behavioral changes were also observed in dingoes (Canis lupus dingo) controlled by Invasive species control remains an essential management tool with reported successes (Britton et al. 2011;Kopf et al. 2017). However, when complete eradication is not achieved through control efforts, re-established populations may contain individuals with traits different from those observed during the precontrol period. By extending the framework of Palkovacs et al. (2018) to invasive species, practitioners of ecosystem-based management would be able to explicitly consider ecological impacts of harvestdriven trait changes when assessing the net efficiency of invasion control techniques, by comparing the benefits of population size reduction versus the risks of harvest-driven trait changes.

  de l'Université Paul Sabatier -Toulouse III et s'est appuyée sur le projet ERADINVA (Office Français pour la Biodiversité -OFB), le projet DISPERSINVA (Agence de l'Eau Adour-Garonne et UNPG) et le projet EC2CO STOECHIOINVA (CNRS INEE). Cette thèse est composée d'une Introduction générale (Chapitre I), d'une présentation des modèles et des sites d'étude (Chapitre II), de quatre chapitres sous la forme d'articles scientifiques (Chapitres III, IV, V et VI) et d'une Discussion générale (Chapitre VII). Une partie de l'Introduction générale renvoie à un article publié dans Frontiers in Ecology and the Environment (Annexe I). Le Chapitre III est en cours de soumission dans la revue Journal of Applied Ecology. Le Chapitre IV est en cours de soumission dans la revue Freshwater Biology. Le Chapitre V a été publié dans la revue Ecology and Evolution. Enfin, le Chapitre VI est un manuscrit en cours de préparation.

  à toi, à Xavier et à Ivan pour votre soutien quotidien et toutes ces petites choses qui égayent la vie ! Merci au personnel administratif du laboratoire qui a participé à faciliter ces trois années et qui a su rendre humains des moments qui auraient pu n'être… qu'administratifs. Merci à Catherine, Pierre, Vincent, Florence. Un merci particulier à Claudine ! Je tiens à remercier Dominique Pantalacci ainsi que Claude Maranges et Hervé Remignon pour avoir toujours été disponibles et à l'écoute, et qui font de l'Ecole Doctorale SEVAB un véritable soutien aux doctorants. Du fond du coeur, merci Dominique.

  Figure I.1 Relations entre variabilités génétique et phénotypique, environnement et fonctionnement de l'écosystème. _____________________________________________________

Figure I. 3 :

 3 Figure I.3 : Représentation schématique des différentes parties de la thèse. Les chapitres III et IV traitent de la variabilité interpopulationnelle et les chapitres V et VI se focalisent sur la variabilité intrapopulationnelle des espèces invasives. ___________________________________

FigureFigure V. 1

 1 Figure IV.S2 MFA analysis of the environmental characteristics of the 23 gravel pit lakes: chlorophyll-a [µg.L -1 ], coexistence [Yes/No], anthropogenic pressure [1/2/3], predation pressure [gillnet biomass per unit effort (BPUE) expressed in g.gillnet -1 .hr -1 ], Faxonius limosus and Procambarus clarkii abundances [catch per unit effort (CPUE) expressed in ind. trap -1 .hr -1 ]. _ 112

Figure V. 2 Figure V. 3

 23 Figure V.2 Frequency distribution of the morphological scores of Procambarus clarkii obtained using a Discriminant Functional Analysis (DFA) between littoral (dark grey) and pelagic (blue) habitats for (a) bodies (n= 140 and n = 137, respectively) and (b) chelae (n= 129 and n = 124, respectively). Body and chela shapes of extreme landmark-based values are displayed (amplified ten times). _______________________________________________________________ 135

Figure VI. 1

 1 Figure VI.1 Comparison of intraspecific variability in (a) response and (b) effect traits (observed values) for Procambarus clarkii (red) females (n = 32) and males (n = 28) and Faxonius limosus (dark yellow) females (n = 28) and males (n = 31). White point and vertical lines represent trait mean and standard deviation, respectively. ___________________________________________

Figure

  Figure VI.S2 Principal component analysis on residuals of the regression of the Procrustes coordinates against log10-transformed centroid sizes, performed in Morpho J v.1.06d (Klingenberg, 2011) and associated body shape variations. Procambarus clarkii individuals are represented in red (n = 63) and Faxonius limosus individuals are in dark yellow (n = 63). ____

Figure I. 1

 1 Figure I.1 Relations entre variabilités génétique et phénotypique, environnement et fonctionnement de l'écosystème.

Figure I. 2

 2 Figure I.2 Représentation schématique du processus d'invasion biologique et des différents types de barrière à travers lesquels les individus sont filtrés. Au cours du processus d'invasion les patrons de variabilité génétique et phénotypique de la population non native sont donc modifiés par rapport à la population native, ce qui peut résulter en des effets différents des individus sur les processus écosystémiques. Les individus non natifs peuvent échouer à chaque étape du processus d'invasion. Adaptée de Lockwood et al. (2007) et Blackburn et al. (2011).

Figure II. 1

 1 Figure II.1 Photo d'une écrevisse américaine Faxonius limosus (à gauche) et d'une écrevisse de Louisiane Procambarus clarkii (à droite). © Rémy Lassus

Figure

  Figure II.2 (a) Cartographie des différents sites utilisés dans le cadre de cette thèse. Les plans d'eau sont légèrement grossis pour être tous distinguables. Photos d'un (b) lac jeune en exploitation d'extraction de granulats et d'un (c) lac mature géré par une fédération de pêche. © Iris Lang

Figure

  Figure III.1, Tables III.S1-2), representing a set of isolated aquatic islands within a terrestrial

Figure III. 1

 1 Figure III.1 Study area with the location (black dots) of all studied lakes for (a) Faxonius limosus and (b) Procambarus clarkii.

Faxonius

  limosus displayed very low levels of genetic diversity (Figure III.2; Table III.S1), with AR averaging 1.470 (SD = 0.217) and Hexp averaging 0.131 (SD = 0.056) across populations. Mean within-population PA values ranged between <0.001 and 0.333 (mean PA across populations of 0.054, SD = 0.08) and mean FstUNI values ranged between 0.088 and 0.235 (mean FstUNI across populations of 0.150, SD = 0.04). Contrastingly, P. clarkii populations displayed higher levels of genetic diversity (Figure III.2; Table III.S2), with AR averaging 3.586 (SD = 0.621) and Hexp averaging 0.596 (SD = 0.082) across populations. Mean PA values ranged between <0.001 and 0.224 (mean PA across populations of 0.04, SD = 0.05), andFstUNI ranged from 0.120 to 0.316 (mean FstUNI value of 0.189, SD = 0.049). The GW statistic was lower than 0.68 for all populations and both species (mean GW across populations of 0.350, SD = 0.076 for F. limosus, and of 0.450, SD = 0.041 for P. clarkii; Tables III.S1-2), suggesting the occurrence of recent genetic bottlenecks in all lakes.

Figure III. 2

 2 Figure III.2 Spatial distribution of allelic richness (AR; a-b), private allelic richness (PA; c-d) and genetic uniqueness (FstUNI; e-f) for Faxonius limosus (a, c and e) and Procambarus clarkii (b, d and f).

  km], FigureIII.3b), suggesting a strong effect of genetic drift and a low homogenizing effect of gene flow on genetic differentiation at short distances.

Figure III. 3

 3 Figure III.3 Pairwise Fst values among populations against Euclidean distances between lakes for (a) Faxonius limosus and (b) Procambarus clarkii. A piecewise regression line (b) is represented in blue (CI95% in grey) as the Mantel test detected a significant IBD pattern for this species. Vertical red dotted line represents the distance at which a breakpoint between two different linear relationships occurs.

  Figure III.S1a) and generated qualitatively similar results; we thus only report results obtained under the most parsimonious model (i.e. "without admixture"). We found strong evidence for K=2 for this species (Figure III.S1b). Overall, there was no clear spatial distribution of these two clusters, nor were populations exclusively belonging to one of these two clusters (Figure III.4a). For P. clarkii, there was a high support for the "without admixture" model (Figure III.S1c) and we found strong evidence for the occurrence of 15 different genetic clusters (Figure III.S1d). These clusters were highly spatially-structured, with many single lake populations (e.g. INN, CEA, VRA, or JBV, Figure III.4b) or groups of neighbouring populations (e.g. SOD, SOC, SOB and SOA for cluster 7; BIR and BID for cluster 4; Figure III.4b) belonging almost-exclusively to specific clusters. There were also some distant populations composed of individuals assigned almost-exclusively to a given cluster (e.g. LIN and BON for cluster 10; Figure III.4b)

  Euclidean distance between lakes (in km) (a) Faxonius limosus in BIR and BID, in TAC and TAD, two populations mainly represented by individuals assigned to cluster 1; Figure III.4b).

Figure III. 4

 4 Figure III.4 Proportion of ancestry of individuals to each cluster identified using 'rmaverick' procedure under a model assuming no admixture: (a) F. limosus (2 clusters) and (b) P. clarkii (15 clusters).

  individuals from specific populations (e.g. for INN, CEA or VRA; Figure III.4b), suggesting that these populations (i) may have been the produce of distinct introduction events (through the release or contaminant pathways) involving genetically-distinct source populations, and/or (ii) have differentiated from those from other lakes due to genetic drift and isolation. Groups of neighbouring populations belonging to the same private owner or experiencing similar management practices (e.g. SOD, SOC, SOB and SOA; BIR and BID; Figure III.4b) were also represented by individuals assigned to specific genetic clusters, hence suggesting that each group originated from specific introduction events, probably through deliberate releases or as contaminants of other commodities. Surprisingly, individuals from PIC and CZB lakes, two lakes belonging to the same private owner, were assigned to the same genetic cluster (cluster 7; Figure III.4b), despite being separated by 33 km, suggesting that deliberate releases (or releases as contaminants) of individuals from the same genetic pool have occurred in these lakes. We further identified individuals that may have been moved as stowaways, or through unaided long-distance dispersal between distant lakes (e.g. 4 individuals from JBV might have moved from GRA/GRB, located 16 km away; Figure III.4b).

Figure

  Figure III.S1 Posterior probabilities of the two different evolutionary models (with/without admixture; a and c) and of the number of K clusters (b and d) tested with 'rmavericK' for Faxonius limosus (a-b) and Procambarus clarkii (c-d).

FigureFigureFigure

  Figure III.S2 Significant interaction terms from the best linear models determined through a backward-selection procedure to explain values of (a) allelic richness (AR) and (b) private allelic richness (PA) observed in Faxonius limosus populations. (a) corresponds to the interactive effects of the Surface of lakes and their Distance to the main city (Toulouse) on AR. Distance is used here as a moderator term, with three values corresponding to the mean Distance value (38.235 km) and to the mean value ± its standard deviation. (b) corresponds to the interactive effects of the Surface of lakes and the strength of fishing Management practices of lakes on PA (grouping levels of the moderator term = Low or High level).

Figure IV. 1

 1 Figure IV.1 Map of the 23 studied gravel pit lakes, southwestern Toulouse, France. Red circles represent Procambarus clarkii populations, yellow circles represent Faxonius limosus populations, and coexisting populations are represented with red and yellow circles.

  [START_REF] Jiang | Microsatellite marker identification from transcriptome derived sequences of the red swamp crawfish, Procambarus clarkii[END_REF] (loci PCSH0005, PCSH0006, PCSH0011, PCSH0038, PCSH0042, PCSH0054, PCSH0077, PCSH0089) and from Hulák et al., (2010) (locus 3.1). Procambarus clarkii neutral genetic variation was assessed using 14 microsatellites following Lang et al.

  clarkii, and two for F. limosus, were co-amplified by Polymerase Chain Reaction (PCR) in final volumes of 10 μL, containing 10-20 ng of genomic DNA, 5 μL of QIAGEN multiplex PCR master mix and locus-specific combination of primers (see Figure IV.S1 for more details). PCR were performed following the procedure described in Lang et al., (2020) (see Figure IV.S1 for the description of the multiplex used in this study). Amplified fragments were analyzed on an ABI PRISM 3730 capillary sequencer (Applied Biosystems, Foster City, USA) at the Génopole Toulouse Midi-Pyrénées.

  characterize individuals' body shapes in further statistical analyses. PC1 and PC2 explained 33.1% and 21.6% of the body morphological variations in P. clarkii, and 54.9% and 11.5% of the variations in F. limosus, respectively (Figure IV.2). Concerning P. clarkii, increasing PC1 scores were associated with stockier body, i.e. shortened abdomen and wider cephalothorax and rostrum, and increasing PC2 scores were associated with a streamlined body morphology, i.e. narrow cephalothorax and more elongated abdomen (Figure IV.2 a). Concerning F. limosus, increasing PC1 scores were associated with stockier body, shortened cephalothorax and more prominent rostrum, and increasing PC2 scores were associated with bigger rostrum, larger cephalothorax and stockier abdomen (Figure IV.2 b).

Figure IV. 2

 2 Figure IV.2 Principal Component Analysis (ACP) based on the covariance matrix of allometry regression residuals for (a) Procambarus clarkii and (b) Faxonius limosus showing the 22 populations and 12 populations, respectively. Body shapes variations (scaling factor: 0.1) along PC1 and PC2 axes are displayed. Populations are colored. Confidence ellipses represent 40% of the variance for each population.

Figure IV. 3

 3 Figure IV.3 Violin plots representing (a) trophic position and (b) terrestrial reliance variations for Procambarus clarkii (red; n = 501) and Faxonius limosus (dark orange; n = 256). Mean trophic position = 2.77 ± 0.64 SE and mean = 3.03 ± 0.53 SE for P. clarkii and F. limosus, respectively. Mean terrestrial reliance = 0.48 ± 0.18 and mean = 0.49 ± 0.18 for P. clarkii and F. limosus, respectively.

Figure IV. 4

 4 Figure IV.4 Stoichiometric niches for (a) Procambarus clarkii and (b) Faxonius limosus. Each sphere represents a population of crayfish, its position represents the mean elemental composition of the population and its volume corresponds to 40% of the variance.

  Figure IV.5 b). For both species, the trophic traits variations were mainly explained at the population level and were almost inexistent at the sex scale (Figure IV.5 a). For F. limosus, the distribution of trophic position variation was more balanced across populations and individual scales (44 % and 53 %, respectively; Figure IV.5 b). For P. clarkii, stoichiometric variations were mainly explained at the individual level (70%, 57%, 62% of the variance for C:N, C:P and N:P ratios, respectively; Figure IV.5 a). For F. limosus, C:P and N:P ratios variations were mainly explained at the individual level (52-58% of the variance). However, C:N ratio variations were equivalently explained at individual and population levels (42 and 44%, respectively; Figure IV.5).

Figure IV. 5

 5 Figure IV.5 Partition of variance of the studied traits (PC1 and PC2 scores, carapace length, trophic position, terrestrial reliance, C:N:P ratios) for (a) Procambarus clarkii (n = 501) and (b) Faxonius limosus (n = 256).

Pst

  were significantly higher than Fst (Psttrophic position = 0.652 (CI95%: 0.386 -0.771) and Pstterrestrial reliance = 0.882 (CI95%: 0.701 -0.952), respectively; Figure IV.6 a). For F. limosus, all groups of traits (i.e. morphological, stoichiometric and trophic traits) were shaped by a combination of adaptive and neutral processes (Figure IV.6 b). Phenotypic differentiations in morphological and stoichiometric traits were higher for F. limosus than for P. clarkii, highlighting that the relative part of adaptive processes shaping the phenotypic variability was more important in F. limosus (Figure IV.7). However, the phenotypic differentiation in P. clarkii was higher for trophic position and terrestrial reliance, indicating that the relative importance of adaptive processes shaping these traits variations in P. clarkii was greater compared to F. limosus (Figure IV.7).

Figure IV. 6

 6 Figure IV.6 Pst estimates for each trait (carapace length, PC1 and PC2 scores, trophic position, terrestrial reliance, C:N, C:P, N:P ratios), and Fst (vertical straight line) on neutral microsatellite markers for (a) Procambarus clarkii (n = 257) and (b) Faxonius limosus (n = 246) from 11 sympatric populations. Horizontal bars represent 95% confident interval of Pst, and vertical dotted line represents 95% confident interval of Fst estimated using a bootstrap procedure.

Figure IV. 7

 7 Figure IV.7 Comparison of Pst estimates for each trait (carapace length, PC1 and PC2 scores, trophic position, terrestrial reliance, C:N, C:P, N:P ratios), between Procambarus clarkii (red; n = 257) and Faxonius limosus (dark orange; n = 246) from 11 sympatric populations. Horizontal bars represent 95% confident interval of Pst estimated using a bootstrap procedure.

Figure

  Figure IV.S1 List of the 14 microsatellites amplified in three PCR multiplex for Procambarus clarkii and of the 9 microsatellites in two PCR multiplex for Faxonius limosus. All primers at 10µM each. Selection based on Belfiore & May (2000) and Jiang et al. (2015) for Procambarus clarkii, and Jiang et al. (2015) and Hulák et al. (2010) for Faxonius limosus.

Figure V. 1

 1 Figure V.1 Conceptual diagram of the establishment of resource polymorphism during the different stages of a biological invasion. Resource polymorphism might result in stable resource polymorphism or in the existence of distinct subpopulations. Adapted from[START_REF] Smith | Evolutionary significance of resource polymorphisms in fishes, amphibians, and birds[END_REF] and[START_REF] Lockwood | Invasion Ecology[END_REF].

(

  BPUE) expressed in g gillnet -1 hr -1 ; Appendix 1). Based on gape limitation and knowledge about trophic interactions in these studied lakes, potential crayfish predators were juveniles and adults of pike Esox lucius (> 275 mm FL), common carp Cyprinus carpio (all individuals), European perch Perca fluviatilis (> 110 mm FL), pikeperch Sander lucioperca (> 200 mm FL), largemouth bass Micropterus salmoides (> 105 mm FL -fork length), and European catfish

V

  .3a). Chela morphology also differed significantly between littoral and pelagic individuals (DFA; T-square = 23.7; P = 0.014). Individuals from littoral habitat displayed lower DFA scores than those from pelagic (mean = -0.19 ± 0.05 SE and 0.19 ± 0.06 SE, respectively), indicating that chelae from littoral individuals were thicker while those from pelagic individuals were more elongated(Figure V.2b). The effect of habitat on chela shape was not sex-dependent (LMM, interaction term: F1,246 = 0.0035, P = 0.953) but DFA chela scores also differed significantly between females and males (LMM, F1,248 = 43.56, P < 0.001), with females displaying higher DFA chela scores than males (mean = 0.39 ± 0.05 SE and -0.23 ± 0.05 SE, respectively; Figure V.3b).

Figure V. 2

 2 Figure V.2 Frequency distribution of the morphological scores of Procambarus clarkii obtained using a Discriminant Functional Analysis (DFA) between littoral (dark grey) and pelagic (blue) habitats for (a) bodies (n= 140 and n = 137, respectively) and (b) chelae (n= 129 and n = 124, respectively). Body and chela shapes of extreme landmark-based values are displayed (amplified ten times).

Figure V. 3

 3 Figure V.3 Boxplot of DFA scores for (a) bodies (nfemales = 121 and nmales = 156) and (b) chelae (nfemales = 108 and nmales = 145) for female and male individuals captured in littoral (dark grey) and pelagic (blue) habitats.

Figure V. 4

 4 Figures V.4b, Figure Appendix V.5).

  Figure Appendix V.3Carapace length (mm) of crayfish from littoral (dark grey) and pelagic (blue) habitats in the 7 gravel pit lakes. The boxplot indicates the median (horizontal bar), the first and third quartiles (box), and the maximum and the minimum values no further than 1.5 x inter-quartile range (whiskers). Dots represent outliers.

  larger chelae), and decreasing "body height/ carapace length" (i.e. more elongated individuals; Figure VI.S3).Chela strength was measured as pinching force of crayfish prior to placing individuals in their own tank, on one occasion in order to reduce the stress of individuals before subsequent measurements throughout the experiment. Individuals were induced to pinch a sensor (Magtrol SA, Switzerland), by holding them by the cephalothorax and inserting the device in their right chela following[START_REF] Malavé | Size, shape, and sex-dependent variation in force production by crayfish chelae[END_REF] and[START_REF] Závorka | Phenotypic responses of invasive species to removals affect ecosystem functioning[END_REF]. Each individual was given sufficient time to produce maximum pinching force and this was recorded to nearest 0.001 N. The maximum pinching force was then corrected by the chela weight (g).

PO4 3 -

 3 excretion to synthetize nutrient excretion, using the score on the first axis which explained 81.2% of the variance. Increasing values on the first axis were associated with increasing excretion rates (Figure VI.S3).

VI. 1

 1 ). Finally, chela strength and growth rate did not differ significantly between the two species (TableVI.1; Figure VI.1).

Figure VI. 1

 1 Figure VI.1 Comparison of intraspecific variability in (a) response and (b) effect traits (observed values) for Procambarus clarkii (red) females (n = 32) and males (n = 28) and Faxonius limosus (dark yellow) females (n = 28) and males (n = 31). White point and vertical lines represent trait mean and standard deviation, respectively.

Figure VI. 2

 2 Figure VI.2 Representation of the functional syndrome for (a) Procambarus clarkii (goodness-of-fit of overall model = 0.38) and (b) Faxonius limosus (goodness-of-fit of overall model = 0.35), based on the PLS-PM model assessing the relationship between response and effect syndromes. The path coefficient is displayed on the arrow linking response and effect syndromes. Each trait contributes to response and effect syndromes according to the loading displayed on arrows. CI95% based on 1000 bootstraps are displayed in brackets. Significant path coefficients and loadings are reported in bold.

  Figure VI.S2 Principal component analysis on residuals of the regression of the Procrustes coordinates against log10-transformed centroid sizes, performed in Morpho J v.1.06d (Klingenberg, 2011) and associated body shape variations. Procambarus clarkii individuals are represented in red (n = 63) and Faxonius limosus individuals are in dark yellow (n = 63).

  chez P. clarkii (Chapitre IV et analyses préliminaires ; Figure VII.1). Bien que des analyses plus poussées sont nécessaires, ces nouveaux résultats tendent à confirmer la supériorité compétitive de P. clarkii pour l'accès à la ressource. Dans les écosystèmes où les deux espèces coexistent, il existe une différence significative de l'utilisation de la ressource de F. limosus, qui possède une plus faible proportion de carbone d'origine terrestre dans son régime alimentaire par rapport aux populations allopatriques (Figure VII.1). Cela suggère que F. limosus est contrainte de se nourrir dans une partie plus centrale des lacs, alors que P. clarkii se maintient dans une zone littorale plus favorable, où la disponibilité des ressources est plus grande et où l'habitat est plus structuré (voir Chapitre V). En revanche, la compétition avec P. clarkii n'entraîne pas de différence sur la position trophique de F. limosus par rapport aux populations allopatriques.

Figure VII. 1 Faxoniuslimosus

 1 Figure VII.1 Comparaison des positions trophiques (trophic position) et de l'origine du carbone utilisé de (a) Procambarus clarkii et (b) Faxonius limosus entre populations allopatriques (une seule espèce d'écrevisse) et sympatriques (coexistence des deux espèces d'écrevisses) faite sur 28 lacs (13 populations sympatriques et 12 et 3 populations allopatriques pour P. clarkii et F. limosus respectivement).

Figure VII. 2

 2 Figure VII.2 Design expérimental proposé pour évaluer les impacts sur les communautés d'invertébrés et le fonctionnement de l'écosystème d'individus des espèces P. clarkii (rouge) et F. limosus (jaune) provenant de populations allopatriques ou sympatriques. Le traitement sympatrique est représenté par le dégradé de couleur (orange), le traitement allopatrique est représenté par une couleur unie (rouge ou jaune). Chaque cercle représente un mésocosme contenant 4 individus avec un sex ratio équilibré. Les 3 mésocosmes sans écrevisse servant de contrôle pour la taille d'effet ne sont pas représentés ici.

  et nos résultats vont dans ce sens puisque nous avons mis en évidence une forte adaptation locale aux ressources trophiques après moins de 30 ans de colonisation chez F. limosus et P. clarkii, qui peuvent toutes deux avoir jusqu' à deux générations par an (Chapitres IV, V ; Souty-Grosset et al., 2006). Bélouard et al. (2019) ont montré que la dispersion naturelle pouvait être limitée une fois que les individus sont établis dans des écosystèmes isolés. La limitation des flux de gènes pourrait donc être suffisante pour permettre l'adaptation locale, malgré les transferts « aidés » d'individus entre populations dues aux diverses activités humaines (Chapitre III). Il serait également intéressant de quantifier le rôle d'une potentielle adaptation épigénétique chez les deux espèces d'écrevisses, en particulier chez F. limosus qui, malgré sa faible diversité génétique, possède une forte capacité d'adaptation[START_REF] Marin | Biological invasion: the influence of the hidden side of the (epi)genome[END_REF]. Jusqu'à présent, peu d'études se sont intéressées à la variation intraspécifique des espèces invasives à une échelle locale. Améliorer notre connaissance à ce niveau est essentiel, tant d'un point de vue théorique que pour adapter les pratiques de gestion des espèces invasives à la meilleure échelle possible.

Figure VII. 3

 3 Figure VII.3 Relations entre variabilités génétique et phénotypique au cours du processus d'invasion. Adapté de Vellend & Geber (2005) et Marin et al. (2019).

Figure 1 .

 1 Figure 1. Examples of effects on community structure and ecosystem functions induced by changes in the traits of invasive species targeted by selective invasion control techniques. (a) Elevated crepuscular activity in lionfish (Pterois volitans) increases the chance of the predator to encounter native reef fishes. (b) Changes in behavioral, morphological, and life-history traits of red swamp crayfish (Procambarus clarkii) affect the leaf-litter decomposition rate in invaded lakes. (c) Changes in life history and diet of pumpkinseed sunfish (Lepomis gibbosus) alter nutrientmediated effects on ecosystem processes.

  2012), and the remaining individuals can re-establish populations (or colonize previously unoccupied habitats) from a pool of individuals with strongly harvest-biased phenotypic traits.

Table Appendix V.2

 Appendix List of the 14 microsatellites amplified in three PCR multiplex. All primers at 10µM each. Selection based on

Table VI .1

 VI Results of the linear mixed models testing the effect of species and sex on response (body morphology, chela strength, growth rate, behavior, and metabolism) and effect trait (excretion, elemental composition, trophic position, consumption rate and bioturbation) traits. Significant P values are in bold. σ 2 Round corresponds to the variance between rounds of the experiment (intercept), and σ 2 Residual corresponds to the variance within rounds (residual). ___ 164

Table VI .2

 VI Spearman correlations among response traits (body morphology, chela strength, growth rate, behavior, and metabolism) for Procambarus clarkii (n = 60) and Faxonius limosus (n = 59). Significant correlations are displayed in bold. ____________________________________ 167

Table VI .

 VI S1 (a) Covariance matrix of response traits for Procambarus clarkii and Faxonius limosus and (b) covariance matrix of effect traits for Procambarus clarkii and Faxonius limosus. Significant covariations are displayed in bold. _________________________________________ 174

? Variabilité génétique Variabilité phénotypique Dynamique et structure des communautés Fonctionnement de l'écosystème x Environnement Fréquence Trait

Fonctionnement de l'écosystème Caractéristiques environnementales Histoire d'invasion Chapitre III Chapitre IV Variabilité génétique Interpopulation Intrapopulation Variabilité phénotypique Interpopulation Chapitre VI Chapitre V Intrapopulation Chapitre II Espèces modèles et sites d'étude Espèce modèles L'écrevisse américaine, Faxonius limosus

	Objectifs
	L'objectif général de cette thèse était de décrire les patrons de variabilité intraspécifique au
	sein de deux métapopulations, d'identifier les déterminants de la variabilité intraspécifique L'écrevisse américaine (spiny cheek crayfish en anglais) est originaire d'Amérique du Nord.
	d'espèces invasives, et de mieux comprendre son implication sur le fonctionnement Elle a été introduite avec succès pour la première fois en Europe vers 1890 en Pologne, où
	d'écosystèmes dulçaquicoles. Ce travail est fondé sur l'étude de populations invasives 90 individus ont été relâchés délibérément dans un étang dans le cadre d'une mesure prise
	d'écrevisses de Louisiane (Procambarus clarkii) et d'écrevisses américaines (Faxonius par la United States Commission of Fish and Fisheries
	limosus) établies en Haute-Garonne, ainsi que sur une approche expérimentale pour évaluer
	, lorsque l'éradication n'est pas complète malgré les efforts de lutte, les les syndromes fonctionnels de chaque espèce.
	populations rétablies peuvent comporter des individus avec des traits différents de ceux
	présents dans la population avant la tentative d'éradication. Il serait pertinent d'appliquer La thèse est structurée en deux parties comprenant un total de 4 chapitres. La première partie
	le cadre conceptuel proposé par Palkovacs et al. (2018) à la gestion des espèces invasives concerne l'étude la variabilité intraspécifique à l'échelle inter-populationnelle (Chapitres IIII,
	pour prendre en compte les impacts écologiques liés aux changements de traits induits IV) et la seconde partie de la thèse se focalise sur la variabilité intra-populationnelle (Chapitres
	par la pression d'éradication. Lors de l'évaluation nette des techniques de contrôle des V, VI ; Figure I.3). Le premier objectif était d'identifier les déterminants environnementaux de
	invasions biologiques, cela permettrait de comparer les avantages d'une réduction de taille la variabilité génétique des deux espèces invasives. Dans ce premier chapitre nous avons
	de population et les risques liés aux modifications phénotypiques induites par la pression également montré l'intérêt et les limites de la génétique des populations pour la reconstitution Figure I.3 : Représentation schématique des différentes parties de la thèse. Les chapitres III et IV d'éradication. traitent de la variabilité interpopulationnelle et les chapitres V et VI se focalisent sur la variabilité d'histoires locales d'invasion, et la déduction précise des routes et vecteurs d'invasion à intrapopulationnelle des espèces invasives.
	l'échelle de la métapopulation (Chapitre III). Le deuxième objectif était de quantifier la
	Il apparaît essentiel de prendre en compte explicitement la variabilité génétique et variabilité phénotypique à différentes échelles d'organisation chez les deux espèces invasives
	phénotypique des espèces invasives, et de décrire les covariations de traits pour ces espèces et d'identifier les facteurs environnementaux et les processus évolutifs (neutres ou adaptatifs)
	afin d'améliorer notre capacité à comprendre leur potentiel d'invasion dans différents à l'origine de ces variations pour différents groupes de traits (morphologiques, trophiques et
	environnements, les dynamiques éco-évolutives impliquées dans les processus d'invasion et stoechiométriques ; Chapitre IV). Le troisième objectif était d'étudier l'existence d'un
	leurs conséquences sur le fonctionnement des écosystèmes. polymorphisme de ressource chez une des espèces invasives (Procambarus clarkii) établie
	récemment, en quantifiant les différenciations morphologiques et trophiques le long de l'axe
	littoral-pélagique benthique (Chapitre V). Enfin, nous avons comparé les structures de
	covariation de traits chez les deux espèces d'écrevisse dans un contexte de coexistence, afin
	de mieux comprendre leurs rôles écologiques respectifs sur le fonctionnement de
	l'écosystème. Pour cela, nous avons utilisé une approche expérimentale de façon à quantifier
	de multiples traits de réponse et traits d'effet chez des individus invasifs, puis d'estimer leurs
	impacts sur le fonctionnement de l'écosystème en utilisant le cadre conceptuel du syndrome
	fonctionnel (Chapitre VI).

  increases with increasing distance in lakes with high level management (Figure III.S3b). Surface of lakes did not affect AR in lakes with low level management, although it had a strong positive effect on AR in lakes experiencing high level management (Figure III.S3a). All three interaction terms were also significant for FstUNI of P. clarkii (Distance x Surface: F1,36=5.2435, Table III.S3). Specifically, FstUNI decreases with increasing lake surface irrespective of the distance of lakes from Toulouse (Figure III.S4a). Conversely, FstUNI increases with increasing distance from Toulouse in lakes experiencing low level management, but decreases with increasing distance in lakes experiencing high level management (Figure III.S4b). FstUNI decreases with increasing lake surface irrespective of the level of management, although the decrease is steeper for lakes experiencing high level management (Figure III.S4c).

	(a)		Faxonius limosus
	BIR p=0.028; Distance x Management: F1,36=31.4851, p<0.001; Management x Surface: BID BVI LAM2 FDL LAV LIN BAB BAA CEA LAF CZA SOB SOA SVD SED TOI VRA Ancestry proportions Cluster 0.0 0.2 0.4 0.6 0.8 1.0 1 2 F1,36=5.6676, p=0.023;
																NORTH-TO-SOUTH GARONNE RIVER AXIS												ARIEGE RIVER
	(b)		Procambarus clarkii																																	AXIS		Cluster
	Ancestry proportions	0.0 0.2 0.4 0.6 0.8 1.0	BOC	GIR	INN	TAD	TAC	BIR	BID	BVI	LAM1	LAM2	PIC	BON	FDL	LOU	SAJ	LAV	LAH	POU	SAB	LIN	BAB	BAA	PEY	BAU	SMI	CEA	NOU	LAF	SJU	CZB	SOD	SOC	SOB	SOA	SVD	TOI	NEW	VRA	GRA	PEA	PEB	GRB	JBV	1 2 3 4 9 10 11 12 5 6 7 8 13 14 15
															NORTH-TO-SOUTH GARONNE RIVER AXIS												NORTH-TO-SOUTH ARIEGE RIVER AXIS
	For AR of P. clarkii, all interaction terms were significant (Distance x Surface: F1,36=6.7022,
	p=0.014; Distance x Management: F1,36=19.9144, p<0.001; Management x Surface:
	F1,36=18.7135, p<0.001; Table III.S3). Specifically, AR increases with increasing lake surface

.S3). Specifically, AR decreases with increasing lake surface in lakes close to Toulouse (Figure III.S2a), while AR increases with increasing lake surface in lakes farther from Toulouse

(Figure III.S2a)

. We also found a significant interaction term (Management x Surface: F1,12=4.9458, p=0.046) for PA of F. limosus (Table

III.S3

). PA increases with increasing lake surface in lakes with a high-level management (Figure III.S2b), but PA decreases with increasing lake surface in lakes with a low-level management (Figure III.S2b). We did not find significant effects of the environmental variables on FstUNI of F. limosus (Table

III

.S3).

irrespective of the distance of lakes from Toulouse

(Figure III.S3a)

. AR steadily decreases with increasing distance from Toulouse in lakes with low level management, and inversely

Table III .

 III S2 Populations of Procambarus clarkii with information about lakes (Code, date of Creation, Latitude, Longitude and their level of fishery Management) and genetic analyses (sampling sizes (N), mean allelic richness (AR), expected heterozygosity (Hexp), mean private allelic richness (PA), mean genetic uniqueness (FstUNI) and mean Garza-Williamson statistic (GW)). A minimum sample size of was considered for rarefaction procedures to obtain AR and PA estimates.

	TAD		43.3300972 1.1458884 Low level	48 4.435	0.690 0.088	0.152 0.491
	TOI		43.0503217 0.5728948 Low level	14 2.448	0.452 <0.001 0.269 0.388
	VRA		43.2445421 1.2510805 Low level	38 3.285	0.601 0.010	0.205 0.401
				Mean	27 3.586	0.598 0.043	0.189 0.450
				SD	7 0.621	0.082 0.050	0.049 0.041
	Site	Creation Latitude	Longitude Management N AR	Hexp PA	FstUNI GW
	BAA		43.1920456 1.1207434 High level	34 3.937	0.649 0.018	0.151 0.469
	BAB		43.1927948 1.1216776 Low level	24 3.692	0.626 0.006	0.158 0.458
	BAU		43.1901757 1.1156223 Low level	30 3.650	0.616 0.0026 0.167 0.373
	BID		43.3132063 1.1707778 High level	35 4.445	0.713 0.122	0.168 0.467
	BIR		Latitude 43.3149184 1.1723150 High level Longitude Management N AR 28 4.562	Hexp PA 0.714 0.067 FstUNI GW NMONO 0.165 0.473
	BAA BOC	1984	43.1920456 1.1207434 High level 43.696586 1.391384 High level	31 1.231 0.067 0.029 20 3.976 0.634 0.048 0.210 0.290 5 0.211 0.380
	BAB BON	1998	43.1927746 1.1216025 Low level 43.2713507 1.1625212 Low level	23 1.267 0.079 0.023 29 3.769 0.632 0.018 0.162 0.427 5 0.142 0.458
	BID BVI	1993	43.3132063 1.1707778 High level 43.3109127 1.2116333 High level	22 1.568 0.163 0.101 27 2.649 0.412 <0.001 0.313 0.575 0.120 0.262 3
	BIR CEA	1992	43.3149184 1.1723150 High level 43.1705748 1.1043968 Low level	21 1.550 0.137 0.095 28 2.850 0.525 0.005 0.106 0.262 4 0.239 0.414
	BVI CZB	1963	43.3109127 1.2116333 High level 43.1347129 1.0540092 Low level	53 1.605 0.164 0.027 28 2.775 0.512 0.054 0.113 0.301 2 0.248 0.473
	CEA FDL	1970	43.1705748 1.1043968 Low level 43.2623928 1.1809382 High level	30 1.392 0.112 <0.001 0.110 0.407 5 46 4.046 0.633 0.066 0.154 0.500
	CZA GIR	1973	43.1336084 1.0536924 Low level 43.3347052 1.2459544 High level	14 1.321 0.083 0.069 19 3.713 0.624 0.050 0.140 0.377 5 0.190 0.412
	FDL GRA	1980	43.2623928 1.1809382 High level 43.235802 1.2608448 High level	23 1.448 0.157 <0.001 0.181 0.504 5 28 2.406 0.399 0.008 0.316 0.430
	LAF GRB	1982	43.1657828 1.1032664 Low level 43.2353916 1.2628752 High level	27 1.154 0.067 <0.001 0.158 0.343 6 18 3.327 0.567 <0.001 0.187 0.401
	LAM2 1987 INN	43.3021334 1.2028925 High level 43.321721 1.3050378 High level	48 1.604 0.149 0.055 17 2.712 0.544 0.077 0.113 0.304 3 0.249 0.399
	LAV JBV	1992	43.2311011 1.1557208 High level 43.170465 1.3307898 Low level	17 1.245 0.073 0.001 34 3.062 0.512 0.006 0.190 0.167 4 0.237 0.441
	LIN LAF	1987	43.2035470 1.1337380 High level 43.1657828 1.1032664 Low level	51 1.400 0.094 0.022 27 3.368 0.599 <0.001 0.171 0.424 0.193 0.357 4
	SED LAH	1976	43.0606415 0.4150075 High level 43.2305593 1.1624622 Low level	29 1.920 0.260 0.333 29 4.189 0.652 0.054 0.158 0.375 2 0.139 0.491
	SOA LAM1	1986	43.1220218 1.0224061 Low level 43.3022554 1.2014410 High level	24 1.272 0.106 <0.001 0.155 0.391 6 12 3.270 0.527 0.021 0.240 0.407
	SOB LAM2	1992	43.1227472 1.0247659 Low level 43.3021334 1.2028925 High level	48 1.600 0.186 <0.001 0.235 0.412 4 28 3.107 0.538 0.013 0.240 0.431
	SVD LAV	1958	43.1113178 1.0018878 High level 43.2311011 1.1557208 High level	11 1.340 0.078 0.029 28 4.378 0.699 0.073 0.137 0.367 5 0.131 0.471
	TOI LIN	1997	43.0503217 0.5728948 Low level 43.203547 1.1337380 High level	18 1.795 0.194 0.049 28 3.325 0.578 0.125 0.088 0.388 2 0.197 0.457
	VRA LOU	1982	43.2445421 1.2510805 Low level 43.2318786 1.1630981 High level	24 1.755 0.196 0.127 28 3.960 0.614 0.025 0.135 0.359 1 0.166 0.485
	NEW		Mean 43.2926411 1.2331285 Low level	29 1.470 0.131 0.054 28 4.086 0.688 0.068 0.150 0.350 4 0.144 0.447
	NOU		SD 43.1654923 1.1018183 Low level	13 0.217 0.056 0.080 27 3.021 0.482 0.079 0.040 0.076 2 0.238 0.453
	PEA		43.2343908 1.2518984 Low level	26 3.876	0.662 0.025	0.157 0.461
	PEB		43.2349956 1.2517832 Low level	17 3.948	0.671 0.001	0.150 0.475
	PEY		43.1915169 1.1141565 Low level	29 3.681	0.641 0.007	0.163 0.416
	PIC		43.285232	1.1850026 Low level	31 4.008	0.667 0.102	0.159 0.504
	POU		43.2218941 1.1530503 High level	30 4.482	0.711 0.031	0.120 0.499
	SAB		43.2152621 1.1504806 Low level	25 4.106	0.673 0.001	0.135 0.459
	SAJ		43.2320905 1.1644074 Low level	30 3.778	0.604 0.037	0.172 0.507
	SJU		43.1551368 1.0805472 Low level	30 3.024	0.540 0.015	0.206 0.422
	SMI		43.1826343 1.1130333 Low level	28 3.974	0.660 0.013	0.131 0.410
	SOA		43.1220218 1.0224061 Low level	27 3.044	0.518 0.133	0.215 0.472
	SOB		43.1227472 1.0247659 Low level	27 3.053	0.560 <0.001 0.204 0.408
	SOC		43.1232123 1.0220173 Low level	28 2.824	0.508 0.005	0.228 0.507
	SOD		43.1238749 1.0239614 Low level	28 3.142	0.543 0.159	0.237 0.443
	SVD		43.1113178 1.0018878 High level	18 3.960	0.631 <0.001 0.133 0.445
	TAC		43.3301296 1.1525397 Low level	28 4.875	0.717 0.224	0.149 0.473

Table III .

 III S3 Selected linear models explaining AR and PA values observed in Faxonius limosus. No models with significant sources of variations were found for FstUNI for this species. Non-italic values correspond to p-values obtained through F-tests using the 'anova' function in R, while p-values reported in italic correspond to p-values obtained through T-tests using the 'summary.lm' function in R (only reported for the factor variable Management and for the Intercept of models). Significant pvalues are in bold.

	Dependent	Explanatory variable	Df	Estimate (SE)	F value	p-value
	variable
	AR	Distance	1	-9.242x10 -6 (<0.0001)	0.4854	0.066
		Management	1		0.713	0.414
		Low level		-6.626 x10 -2 (0.0951)		0.498
		Surface	1	-2.565x10 -6 (<0.0001)	0.9324	0.352
		Distance x Surface	1	8.645x10 -11 (<0.0001)	8.0014	0.014*
		Intercept		1.756 (0.1786)		<0.001***
		Residuals (Error)	13
	PA	Distance	1	-2.922x10 -6 (<0.0001)	0.5154	0.487
		Management	1		2.6667	0.128
		Low level		0.1167 (0.1218)		0.357
		Surface	1	-1.065x10 -7 (<0.0001)	0.1136	0.742
		Distance x Surface	1	4.388x10 -11 (<0.0001)	2.5117	0.139
		Management x Surface 1		4.9458	0.046*
		S x Low level		-2.152x10 -6 (<0.0001)		0.046*
		Intercept		0.2649 (0.1282)		0.061
		Residuals (Error)	12
	FstUni	Distance	1	3.266x10 -7 (<0.0001)	0.3214	0.580
		Management	1		0.1979	0.663
		Low level		-0.0086 (0.0021)		0.701
		Surface	1	8.162x10 -8 (<0.0001)	0.311	0.586
		Intercept		0.1326 (0.0257)		<0.001***
		Residuals (Error)	14

Table III .

 III S4 Best linear models (after a backward-selection procedure) explaining AR and FstUNI values observed in Procambarus clarkii. No models with significant sources of variations were found for PA for this species. Non-italic values correspond to p-values obtained through F-tests using the 'anova' function in R, while p-values reported in italic correspond to p-values obtained through T-tests using the 'summary.lm' function in R (only reported for the factor variable Management and for the Intercept of models). Significant p-values are in bold.

	Dependent	Explanatory variable	Df	Estimate (SE)	F value	p-value
	variable
	AR	Distance	1	2.608 (0.2689)	16.3893	<0.001***
		Management	1		0.753	0.391
		Low level		2.390 (0.3856)		<0.001***
		Surface	1	4.857x10 -6 (<0.0001)	1.7039	0.200
		Distance x Surface	1	7.127x10 -11 (<0.0001)	6.7022	0.014*
		Distance x Management	1		19.9144	<0.001***
		D x Low level		-6.278x10 -5 (<0.0001		<0.001***
		Management x Surface	1		18.7135	<0.001***
		S x Low level		-6.833x10 -6 (<0.0001)		<0.001***
		Intercept		2.608 (0.2689)		<0.001***
		Residuals (Error)	36
	PA	Distance	1	-2.347x10 -6 (<0.0001)	3.186	0.082
		Management	1		0.1278	0.723
		Low level		0.0125 (0.0429)		0.773
		Surface	1	1.05x10 -7 (<0.0001)	0.2596	0.613
		Intercept		0.2203 (0.0476)		<0.001***
		Residuals (Error)	39
	FstUni	Distance	1	7.449x10 -5 (<0.0001)	1.3740	0.249
		Management	1		1.2683	0.2675
		Low level		5.418 (0.9104)		<0.001***
		Surface	1	4.582x10 -6 (<0.0001)	1.2152	0.2776
		Distance x Surface	1	2.308x10 -10 (<0.0001)	5.2435	0.028*
		Distance x Management	1		31.4851	<0.001***
		D x Low level		-1.641x10 -4 (<0.0001)		<0.001***
		Management x Surface	1		5.6676	0.0227*
		S x Low level		-8.879x10 -6 (<0.0001)		0.023*
		Intercept		2.979 (0.6349)		<0.001***
		Residuals (Error)	36

Table IV .

 IV 1 Environmental, historical and management characteristics of the 23 sampled lakes.

	Population	Year of lake creation	Productivity µg.L -1	CPUE P. clarkii ind. trap -1

.hr -1 CPUE F. limosus ind. trap -1 .hr -1 BPUE predation g.gillnet - 1 .hr -1 Management type Anthropogenic pressure

									Coexistence
									of P. clarkii
									and
									F. limosus
	BAA	1990	21.78	0.44	0.61	184.228	Federal	3	Yes
	BAU	2000	2.03	4.28	0.00	18183.510	Private	1	No
	BID	1992	10.90	0.67	0.00	11.878	Federal	3	No
	BIR	1992	3.43	7.00	0.67	2156.477	Federal	3	Yes
	BON	1990	5.00	0.33	0.00	581.871	Communal	2	No
	BVI	1963	73.92	2.94	3.72	5258.807	Federal	3	Yes
	CEA	1971	0.85	3.97	1.44	407.540	Private	1	Yes
	CZA	1973	2.95	0.00	0.00	64.156	Private	1	No
	CZB	2008	2.80	0.11	0.00	0	Private	1	No
	LAF	1982	1.63	1.69	2.00	2106.577	Private	1	Yes
	LAH	1972	1.32	14.72	0.06	596.239	Private	1	No
	LAM2	1987	10.45	60.22	0.00	1323.978	Federal	3	Yes
	LAV	1992	1.78	8.56	0.11	189.706	Communal	2	Yes
	LIN	1990	43.80	0.75	0.83	263.392	Federal	3	Yes
	PEY	2007	4.20	5.67	0.00	1376.866	Communal	2	No
	POU	1996	2.68	3.33	0.00	360.520	Communal	2	No
	SAB	2006	8.02	4.86	0.00	28.64739	Communal	2	No
	SAJ	1983	10.18	3.28	0.00	0	Private	1	No
	SOA	1993	36.90	5.11	3.00	1442.952	Private	1	Yes
	SOB	1998	0.68	10.50	1.61	842.013	Private	1	Yes
	SOC	2005	4.38	4.39	0.00	1468.924	Private	1	No
	SOD	2007	2.53	3.11	0.00	399.820	Private	1	No
	VRA	1982	38.05	0.39	0.56	1590.484	Private	1	Yes

  Figure IV.S2 MFA analysis of the environmental characteristics of the 23 gravel pit lakes: chlorophylla [µg.L -1 ], coexistence [Yes/No], anthropogenic pressure [1/2/3], predation pressure [gillnet biomass per unit effort (BPUE) expressed in g.gillnet -1 .hr -1 ], Faxonius limosus and Procambarus clarkii abundances [catch per unit effort (CPUE) expressed in ind. trap -1 .hr -1 ].

		PclG-27 F PclG-28 R PCSH0089 F PCSH0077F		0.15 0.1 0.1 0.08
	PclG-27 R PclG-16 F PclG-16 R PclG-04 F PclG-04 R Multiplex 2 Procambarus clarkii Locus GenBank accession number PclG-32 F PclG-32 R PCSH0038 F PCSH0038 R Multiplex 3 Procambarus clarkii Locus GenBank accession number PCSH0089 R PCSH0006 F PCSH0077R PCR MIX PCSH0006 R PCSH0005 F Multiplex 2 Faxonius limosus H2O Qiagen multiplex PCR Master Mix PCSH0005 R GenBank accession DNA Locus number PCSH0005F PCSH0005R Multiplex 1 Faxonius limosus Locus GenBank accession number PCSH0005 KP675955 PCSH3.1 AY112995 PCSH3.1F PCSH3.1R Predation pressure Allele size range (bp) Allele size range (bp) Volume (µL) x1 0.15 0.1 0.1 0.1 0.1 Forward Primer (5'-3') 0.1 0.1 0.1 0.1 Forward Primer (5'-3') 0.1 0.08 0.1 0.1 2.24 5 0.1 Allele size 2 0.1 Forward Primer (5'-3') 0.08 range (bp) 0.08 Allele size Forward Primer (5'-3') 100-160 AAC AGA GTG GCA AGG TAC TTG AA 284-374 TTC AGG GGC GAG AAA GTT GTG AC 0.1 Productivity 0.1 PCSH0042F 0.04 range (bp) PCSH0042 KJ607980 117-177 AGT GAC TCT TTA CTG ATC GCT CG PCSH0042R 0.04 F. limosus abundance	Reverse Primer (3'-5') Reverse Primer (3'-5') PCR cycling conditions 95°C 15 min 94°C 30 s Reverse Primer (3'-5') 56°C 90 s 72°C 60 s Reverse Primer (3'-5') GGC TGT CAC TCG TGT CTT TAG TT GTG GGA AGG GGT AAG GGA GAG 60°C 45 min 10°C ∞ TTA GTG AGG AAG AGG AAG TGG TG	Fluorescent dye Fluorescent dye Fluorescent dye Fluorescent dye FAM FAM ATTO 550
	PclG-29 PclG-48 PCSH0006 PclG-07 PclG-28 PclG-17 PCSH0089 PCSH0011 PCSH0038 PCSH0089 PCSH0054	AF290934 AF290941 KP675956 PCSH0054F AF290922 AF290933 AF290929 KJ607988 KP675961 KJ607979 KJ607988 PCSH0089R PCSH0089F KJ607983 PCSH0054R	159-210 145-175 125-185 112-124 238-266 159-184 80-120 141-201 160-230 85-145 140-200	GAA AGT CAT GGG TGT AGG TGT AAC CTG TTG GTG ATT TCC GTC AAT TTT GGC CAA AAT GTG AAG AGT TGT TA 0.1 CCT CCC ACC AGG GTT ATC TAT TCA CTC GGC GAG TTT ACT GAA AT GTC GGG AAC CTA TTT ACA GTG TAT GTA TAC ACA GCT TTG GAA CTG GG CCT AGC AGC CTT GGT AGT AAC CT CAG AGC ACT GTT TGC TAG TGT GT GTA TAC ACA GCT TTG GAA CTG GG 0.06 0.06 TTG TAA CAA ATG TTT TCT GTG TGC 0.1 Anthropogenic pressure	AGA TTC AAC GCT GTG TTC CTG ATC GAA CCA GAT CAG TGT CAT GTG AG TTT TTG GGC TAT GTG ACG AG GTG GGT GTG GCG CTC TTG TT AGA AGA AAG GGA TAT AAG GTA AAG AAG AGC GAA GAA AGA GAT AAA GAT GCT TCC TCT GTT ATT CAT CAT GC TGA AAG ACG TGA TGT AAA GTT GC GCT TCC TCT GTT ATT CAT CAT GC GCT TCC TCT GTT ATT CAT CAT GC TGG AAG CAC TAG CAC TAC CTT TC	ATTO 550 ATTO 550 FAM FAM HEX HEX HEX HEX HEX ATTO565 ATTO565
	PclG-32 PCSH0006 PCSH0077	AF290935 KP675956 KJ607986	173-221 140-180 125-185	CCC CCA CTC GTC TCT GTG TAT G GGC CAA AAT GTG AAG AGT TGT TA GGG ATA GCA CAA TAC ACT CAT CC	TGT GCT TGC GGG AGT GAG C GAA CCA GAT CAG TGT CAT GTG AG GGG TGC TAT GCA TCA CAT TAA AA	FAM FAM ATTO 550
	PCSH0038 PCSH0005	KJ607979 KP675955	150-190 110-135	CAG AGC ACT GTT TGC TAG TGT GT AAC AGA GTG GCA AGG TAC TTG AA	GCT TCC TCT GTT ATT CAT CAT GC GGC TGT CAC TCG TGT CTT TAG TT	HEX FAM
				P. clarkii abundance
				TAT ATC AGT CAA TCT GTC CAG		FAM
		PCR MIX PCR MIX	Volume (µL) x1 Volume (µL) x1	TCA GTA AGT AGA TTG ATA GAA GG
	PCR MIX H2O Qiagen multiplex PCR Master Mix DNA PclG-15 F PclG-15 R H2O Qiagen multiplex PCR Master Mix DNA PclG-29 F PclG-29 R PclG-07 F PclG-07 R PclG-28F PCR MIX H2O H2O Qiagen multiplex PCR Master Mix Qiagen multiplex PCR Master Mix DNA DNA PCSH0006F PclG-48 F PCSH0006R PclG-48 R PCSH0011F PclG-17 F PCSH0011R PclG-17 R PCSH0038F PCSH0038R	Volume (µL) x1 2.1 5 2 0.1 0.1 2 5 2 0.1 0.1 0.1 0.1 0.1 2.48 Volume (µL) x1 5 2 2 5 0.06 2 0.06 0.1 0.04 0.1 0.04 0.1 0.08 0.1 0.08

Table IV .

 IV S2 Results of the linear models testing the effect of Population and Sex on each phenotypic trait (PC1 and PC2 scores, carapace length, trophic position, terrestrial reliance, C:N:P ratios) for Procambarus clarkii (n = 501) and Faxonius limosus (n = 256). The full model included an interaction term (Sex x Population) which was removed from the final model if non-significant. Significant P values are in bold.

				Sex	1791.5	1	18.866	2.097e-05 ***
				Population:Sex 2697.0	11	2.582	0.004131	**
				Residuals	22030.2	232
		N :P		Population	663.67	11	16.9097 <2,00E-16 ***
				Sex	23.50	1	6.5865	0.01090	*
				Population:Sex 80.94	11	2.0623	0.02392	*
	Species	Phenotypic trait	Predictor Residuals	SumSq 827.78	Df	F	P value
	Species Procambarus clarkii PC1 score BAA F. limosus P. clarkii F. limosus PC2 score BIR P. clarkii BVI F. limosus Carapace length AR 1.31 4.14 1.60 4.58 1.86 P. clarkii 2.82	NA Population 1.38 5.62 Sex Residuals 1.63 Population 6.23 Sex Residuals 2.00 Population 4.46 Sex	Hexp 0.06 0.0157163 21 0.67 0.0015995 1 0.0285089 478 0.11 0.0073204 21 0.71 0.0011634 1 0.0239780 478 0.14 7480.1 21 0.43 446.3 1	Hobs 0.04 12.548 0.67 26.819 0.11 6.9491 0.68 23.1926 1.97e-06 Fis <2.2e-16 0.41 3.299e-07 *** *** 0.02 <2.2e-16 *** 0.05 *** 0.07 0.15 -0.03 11.537 <2.2e-16 *** 0.45 -0.02 14.454 0.0001622 ***
	CEA LAF LAM	F. limosus P. clarkii Trophic position 1.53 2.93 F. limosus 1.21 P. clarkii 3.43 Terrestrial reliance Population 1.63 Residuals 3.85 Population Sex 1.25 Residuals 4.00 Sex F. limosus 1.60 1.63 Residuals P. clarkii 3.13 5.46 C :N Population	0.11 14758.6 0.53 149.769 0.013 0.07 54.321 0.61 13.5258 0.0056 0.13 3.1535 0.54 29.285	478 21 1 478 21 1 478 21	0.13 0.56 62.7568 <2e-16 -0.14 -0.03 0.1123 0.7377 0.05 0.21 0.53 97.6302 <2e-16 0.16 0.8459 0.3582 0.14 -0.06 0.56 -0.02 8.9890 <2.2e-16	*** *** ***
	LAV	F. limosus P. clarkii	1.43 4.48	1.50 Population:Sex 8.071 0.07 Sex 0.842 6.54 0.71 Residuals 70.897	1 21 457	0.08 5.4289 2.4773 0.73	0.0202402 * -0.07 0.0003335 *** -0.01
	LIN SOA	F. limosus C :P P. clarkii F. limosus P. clarkii N :P	1.57 3.43 1.32 3.12	1.63 Population 6.46 Sex Population:Sex 6011 0.09 54431 0.58 3416 1.38 0.11 Residuals 74854 4.69 0.53 Population 1585.5	21 1 21 457 21	0.10 15.8245 <2.2e-16 -0.15 0.52 20.8537 6.383e-06 *** *** 0.12 1.7475 0.02173 * 0.11 -0.02 0.48 0.12 13.162 <2.2e-16 ***
	SOB Faxonius limosus	F. limosus P. clarkii PC1 score	1.70 3.10	1.75 Residuals Sex 4.62 Population	0.19 2741.9 65.2 0.57 0.055630	1 478 11	0.19 11.367 0.61 69.663	0.0008082 *** 0.03 -0.06 <2.2e-16 ***
	VRA	F. limosus P. clarkii PC2 score	2.16 3.35	2.50 5.00 Residuals Sex Population	0.20 0.001770 0.61 0.017641 0.0042398 11 1 243	0.21 24.386 0.63 12.4418 <2.2e-16 1.467e-06 *** -0.04 -0.02 ***
				Sex	0.0027145 1	87.6218 <2.2e-16	***
				Population:Sex 0.0010183 11	2.9883	0.0009767 ***
				Residuals	0.0071872 232
		Carapace length	Population	12096.0	11	26.6983 <2.2e-16	***
				Sex	264.5	1	6.4207	0.011939	*
				Population:Sex 1068.6	11	2.3587	0.008918	**
				Residuals	9555.5	232
		Trophic position	Population	34.368	11	20.4096 <2,00E-16 ***
				Sex	0.591	1	3.8606	0.05057	.
				Residuals	37.199	243
		Terrestrial reliance Population	6.3647	11	80.0690 <2,00E-16 ***
				Sex	0.0217	1	2.9965	0.08472	.
				Residuals	1.7560	243
		C :N		Population	12.6578	11	19.3507 <2.2e-16	***
				Sex	1.7629	1	29.6458 1.318e-07 ***
				Population:Sex 1.3414	11	2.0506	0.02485	*
				Residuals	13.7961	232
		C :P		Population	18748.2	11	17.949	<2.2e-16	***

Table IV .

 IV S3 Results of the linear mixed models testing the effect of environmental variables 1 and 2, and invaded time on each phenotypic trait (PC1 and PC2 scores, carapace length, trophic position, terrestrial reliance, C:N:P ratios) for Procambarus clarkii (n = 501) and Faxonius limosus (n = 256). The full model included double interaction terms which were removed using a backward procedure if nonsignificant. Significant P values are in bold. Increasing value for environmental variable 1 corresponds to increasing anthropogenic pressure, abundance of F. limosus and lake productivity and increasing value for environmental variable 2 corresponds to increasing predation pressure and decreasing abundance of P. clarkii.

			Environmental
			variable 2	1.2098	1	7.9948 0.3034
		PC2 score	Invaded time	0.1691	1	8.1334 0.6915
			Environmental
			variable 1	2.6340	1	8.5838 0.1407
			Environmental
			variable 2	0.1923	1	7.8799 0.6728
		Carapace length	Invaded time	0.0435	1	8.1836 0.83996
			Environmental
	Species Procambarus clarkii Chapitre V Phenotypic trait PC1 score Trophic position PC2 score Carapace length Trophic position Terrestrial reliance C :N N :P C :P C :N Terrestrial reliance	Predictor variable 1 Environmental Invaded time variable 2 Invaded time Environmental variable 1 Environmental variable 1 Environmental variable 2 Environmental Invaded time variable 2 Environmental variable 1 variable 2 Invaded time variable 1 variable 2 Invaded time variable 1 variable 2 variable 1 variable 2 Invaded time variable 2 Environmental Environmental variable 1 Environmental Environmental Invaded time variable 2 Invaded time Environmental variable 1 Environmental Environmental Invaded time Environmental variable 2 Environmental variable 1 Environmental Environmental Invaded time Environmental variable 2 Environmental variable 1 Environmental Environmental Invaded time	F 0.1261 0.0170 8.8947 0.1817 0.1772 0.0369 0.1635 11.1815 1 Df Df.res 1 8.3624 0.73130 P value 1 1 7.9293 0.01771 18.366 0.8977 1 8.2429 0.6808 1 17.806 0.6788 1 8.2585 0.8523 1 17.781 0.6907 0.7224 1 7.9519 0.4202 18.796 0.0034499 ** * 0.1817 0.0369 0.7224 0.3953 1 20.0109 1 0.0001 1 0.0084 1 0.8730 1 2.4648 1 0.2303 1 0.3168 1 0.1124 1 0.9849 1 1.1078 1 1.0206 1 18.536 0.3254 2.1500 1 7.9078 0.1812 2.1500 17.964 0.3065 2.7297 1 8.4601 0.1350 2.7297 17.968 0.3342 0.3736 1 8.1545 0.5577 0.3736 18.067 0.7413 0.9244 1 7.9171 0.3648 0.9244 17.948 0.5805 1.6135 1 8.4178 0.2380 1.6135 17.953 0.6371 0.8502 1 8.1652 0.3829 0.8502 1.1141 1 7.9516 0.3222 1.1141 18.095 0.1337 17.749 0.3627 0.5590 1 8.2602 0.4754 0.5590 17.778 0.9279 0.8654 1 8.2416 0.3787 0.8654 0.5745 1 8.0081 0.4702 0.5745 18.412 0.9942 17.182 0.0003263 *** 0.0033 1 8.0571 0.9558 0.0033 17.304 0.5377600 0.3761 1 9.1564 0.5546 0.3761
			Environmental
			variable 1	0.2079	1	17.694 0.6540
			Environmental
			variable 2	1.6654	1	17.652 0.2135
		C :P	Invaded time	10.4327 1	18.551 0.004511	**
			Environmental
			variable 1	0.8063	1	17.683 0.381294
			Environmental
			variable 2	3.1506	1	17.639 0.093158	.
		N :P	Invaded time	8.6947	1	18.568 0.00839	**
			Environmental
			variable 1	0.5184	1	17.669 0.48093
			Environmental
			variable 2	4.6395	1	17.624 0.04535	*
	Faxonius	PC1 score	Invaded time
	limosus			0.2647	1	8.7212 0.6197
			Environmental
			variable 1	0.3055	1	8.0855 0.5954

Polymorphisme de ressource stable chez une écrevisse envahissante le long de l'axe littoral-pélagique benthique Résumé Bien

  que la variabilité intraspécifique soit maintenant reconnue pour ses effets sur les processus évolutifs et écologiques, notre connaissance de l'importance de la variabilité intraspécifique des espèces envahissantes est encore limitée. Pourtant, la compréhension de

	l'association des divergences morphologiques et trophiques au sein des populations (i.e. le
	polymorphisme de ressource) peut nous aider à mieux appréhender les impacts écologiques
	des individus envahissants sur les écosystèmes natifs. Dans cette étude nous avons quantifié
	l'ampleur du polymorphisme de ressource dans 16 populations lacustres d'une espèce
	d'écrevisse envahissante, Procambarus clarkii, en comparant les traits trophiques (estimés à
	l'aide d'isotopes stables) et morphologiques des individus des habitats littoral et pélagique
	des lacs. Premièrement, nos résultats ont permis de montrer que les écrevisses occupaient

à la fois les habitats littoral et pélagique dans 7 des lacs échantillonnés, et que l'utilisation de l'habitat pélagique était associée à une abondance plus importante des individus dans l'habitat littoral. Ensuite, nous avons montré l'existence de différences morphologiques (la forme du corps et des pinces) et trophiques (utilisation du carbone littoral) entre les individus des habitats littoral et pélagique, mettant ainsi en évidence l'existence d'un polymorphisme de ressource au sein de populations invasives. Il n'existait pas de différenciation génétique entre les individus des deux habitats, permettant donc de conclure à un polymorphisme de ressource stable (flux de gènes important entre les individus). Enfin, nous avons démontré que des processus adaptatifs divergents étaient à l'origine des différences morphologiques du corps et des pinces entre les deux habitats, tandis que les différences d'utilisation de la ressource ont évolué de manière neutre sous la dérive génétique. Ces résultats démontrent que l'écrevisse envahissante P. clarkii possède une très forte variabilité phénotypique dans des populations récemment établies, et ces différences pourraient conduire à des impacts écologiques contrastés entre les individus des habitats littoral et pélagique.

Table V .1

 V Genetic diversity of Procambarus clarkii in the littoral and pelagic habitats based on 14 microsatellites of 7 studied lakes. NA = mean number of alleles per locus, AR = allelic richness, He = expected heterozygosity, Ho = observed heterozygosity, FIS = fixation indices.

	Lake	Habitat	NA	AR	He	Ho	FIS
	A	Littoral 5.0714 4.8065 0.6585 0.6821 -0.010
		Pelagic 5.1429 4.9456 0.6709 0.7120 -0.033
	B	Littoral 4.7143 4.3966 0.5921 0.5918	0.027
		Pelagic 4.6429 4.4206 0.6102 0.5523	0.122
	G	Littoral 6.4286 5.9626 0.7014 0.7297 -0.014
		Pelagic 6.4286 6.0222 0.6898 0.6582	0.073
	I	Littoral 4.8571 4.6441 0.6407 0.6172	0.064
		Pelagic 4.4286 4.1959 0.6181 0.6417 -0.013
	J	Littoral 5.7857 5.4438 0.6897 0.6910	0.026
		Pelagic 6.0000 5.8495 0.7127 0.6964	0.056
	K	Littoral 5.1429 4.7662 0.6480 0.6679 -0.005
		Pelagic 5.2143 4.7738 0.6461 0.6455	0.027
	M	Littoral 3.4286 3.3727 0.5616 0.5438	0.058
		Pelagic 3.7143 3.6164 0.5882 0.6212 -0.030

Table Appendix V

 Appendix .2 List of the 14 microsatellites amplified in three PCR multiplex. All primers at 10µM each. Selection based on[START_REF] Belfiore | Variable microsatellite loci in red swamp crayfish, Procambarus clarkii, and their characterization in other crayfish taxa[END_REF] and[START_REF] Jiang | Microsatellite marker identification from transcriptome derived sequences of the red swamp crawfish, Procambarus clarkii[END_REF].

	Multiplex 2 Multiplex 3
	Multiplex 1 Locus Locus Locus PclG-29 PclG-48	GenBank accession number GenBank accession number GenBank accession number AF290934 AF290941	Allele size range (bp) Allele size range (bp) Allele size range (bp) 159-210 GAA AGT CAT GGG TGT AGG TGT AAC Forward Primer (5'-3') Forward Primer (5'-3') Forward Primer (5'-3') 145-175 CTG TTG GTG ATT TCC GTC AAT TTT	Reverse Primer (3'-5') Reverse Primer (3'-5') Reverse Primer (3'-5') TTT TTG GGC TAT GTG ACG AG AGA TTC AAC GCT GTG TTC CTG ATC	Fluorescent Fluorescent dye dye Fluorescent dye ATTO 550 ATTO 550
	PclG-15 PclG-07 PclG-28 PclG-17	AF290927 AF290922 AF290933 AF290929	120-200 112-124 CCT CCC ACC AGG GTT ATC TAT TCA GGC GTG ACG CCA ACG TGT CTT 238-266 CTC GGC GAG TTT ACT GAA AT 159-184 GTC GGG AAC CTA TTT ACA GTG TAT	GGC TGG CCA CTT TGT TAG CCT GAG GTG GGT GTG GCG CTC TTG TT AGA AGA AAG GGA TAT AAG GTA AAG AAG AGC GAA GAA AGA GAT AAA GAT	ATTO 550 FAM HEX HEX
	PclG-27 PclG-32 PCSH0089	AF290932 AF290935 KJ607988	100-130 173-221 CCC CCA CTC GTC TCT GTG TAT G AAT CTT AAG ATC ATG AAA AAG GTA TTT AAG GAA CGT ATA AGA AAA GAC TGT GCT TGC GGG AGT GAG C 80-120 GTA TAC ACA GCT TTG GAA CTG GG GCT TCC TCT GTT ATT CAT CAT GC	FAM FAM HEX
	PclG-16 PCSH0038 PCSH0006	AF290928 KJ607979 KP675956	80-180 150-190 CAG AGC ACT GTT TGC TAG TGT GT CTC GGA ATG TCC ACC TGA GA 140-180 GGC CAA AAT GTG AAG AGT TGT TA	TCA TTA TGG ATT TTG TCA ATC TAT GCT TCC TCT GTT ATT CAT CAT GC GAA CCA GAT CAG TGT CAT GTG AG	HEX HEX FAM
	PCSH0005	KP675955	110-135	AAC AGA GTG GCA AGG TAC TTG AA	GGC TGT CAC TCG TGT CTT TAG TT	FAM
	PclG-04	AF290921	170-255	TAT ATC AGT CAA TCT GTC CAG	TCA GTA AGT AGA TTG ATA GAA GG	FAM
		PCR MIX	Volume (µL) x1
		H2O		2
	PCR MIX Qiagen multiplex PCR Master Mix PCR MIX	Volume (µL) x1 5 Volume (µL) x1
		H2O DNA H2O	2.1 2 2
	Qiagen multiplex PCR Master Mix PclG-29 F Qiagen multiplex PCR Master Mix	5 0.1 5
		DNA PclG-29 R DNA	2 0.1 2
		PclG-15 F PclG-07 F PclG-48	0.1 0.1
		PclG-15 R PclG-07 R	0.1 0.1
		PclG-27 F PclG-28F	0.15 0.1
		PclG-27 R PclG-28 R	0.15 0.1
		PclG-16 F PclG-32 F	0.1 0.1
		PclG-16 R PclG-32 R	0.1 0.1
		PclG-04 F PCSH0038 F	0.1 0.1
		PclG-04 R PCSH0038 R	0.1 0.1

Covariations de traits fonctionnels chez deux espèces d'écrevisses invasives coexistantes Résumé L

  'importance de la variabilité intraspécifique dans les processus écologiques et évolutifs est maintenant reconnue. Cependant, améliorer notre connaissance de la structure des variations et des covariations des traits de réponse et d'effet (i.e. syndromes fonctionnels) est nécessaire pour bien comprendre les relations intrinsèques entre les différentes fonctions des organismes et leurs effets sur le fonctionnement des écosystèmes. Ceci est particulièrement important dans le contexte des invasions biologiques pour pouvoir mieux appréhender les impacts des espèces invasives sur les écosystèmes natifs. A l'aide d'une expérimentation utilisant une approche multi-traits, nous avons comparé les structures de variations et de covariations de traits de réponse et d'effet de deux espèces d'écrevisse coexistantes, Procambarus clarkii et Faxonius limosus. Globalement, nous avons mis en évidence une forte variabilité intraspécifique chez les deux espèces ainsi qu'une forte variabilité interspécifique.

		19		BAA-CLA-2014 Lake A					BAU-CLA-2014 Lake B
		15
	δ 15 N (‰)	11
		7 7
		3 3
		19		LAV-CLA-2014 Lake G			19		PEY-CLA-2014 Lake I
		15					15
	11 Chapitre VI δ 15 N (‰)				11
		7 7					7
		3 -34 -34 3	-29 -29	-24 -24	-19 -19	-14 -14	3 -34 -34	-29 -29	-24 -24	-19 -19	-14 -14
				δ 13 C (‰)					δ 13 C (‰)
				SOB-CLA-2014 Lake K
		17
	N (‰)	13
	δ 15
		19		POU-CLA-2014 Lake J					SAB-CLA-2014 Lake M
		15
	δ 15 N (‰)	11
		-34 -34	-29 -29	-24 -24	-19 -19	-14 -14	-34 -34	-29 -29	-24 -24	-19 -19	-14 -14
				δ 13 C (‰)				δ 13 C (‰)

Nous avons également montré que les syndromes de réponse et d'effet étaient différents entre les deux espèces, et qu'au sein de chaque espèce ils étaient corrélés pour former des syndromes fonctionnels contrastés. P. clarkii possédait une plus forte covariation de traits que F. limosus. Nos résultats illustrent une forte différence dans les relations existant entre les fonctions des individus des deux espèces, suggérant qu'elles avaient des impacts contrastés sur le fonctionnement de l'écosystème. Nous avons aussi montré que la capacité à prédire les impacts des individus invasifs peut être très variable selon l'espèce considérée.

  Table VI.1). Specifically, F. limosus had higher body morphology scores than P. clarkii individuals (mean = 0.94 ± 0.13 SE and mean = -0.93 ± 0.13 SE for F. limosus and P. clarkii, respectively), indicating that they had overall shorter rostrum and wider cephalothorax than P. clarkii(Figure VI.1; Figure VI.S3a). Compared to P. clarkii, they also display higher "chela height/body height" ratio (mean = 0.40 ± 0.007 SE and mean = 0.36 ± 0.010 SE for F. limosus and P. clarkii, respectively; Appendix 3a) and smaller "body height/carapace length" ratio (mean = 0.39 ± 0.004 SE and mean = 0.44 ± 0.004 SE for F. limosus and P. clarkii, respectively; Figure VI.S3a), indicating that at similar body size, F. limosus individuals had bigger chelae and more elongated body morphology than P. clarkii (which is the deformation also observable along morphometric PC1 axis; Figure VI.S2). The behavioral score was higher in F. limosus than in P. clarkii (FigureVI.1; Figure VI.S3a), indicating that F. limosus individuals were more active than P. clarkii individuals (mean proportion of active time = 60.90 % ± 2.24 SE and mean = 46.93 % ± 2.05 SE for F. limosus and P. clarkii, respectively) and tended to have a higher anxietylike behavior (mean proportion of time in the shadow = 62.85 % ± 2.74 SE, and mean = 59.43 % ± 3.32 SE for F. limosus and P

	, P < 0.001; F1,115.31 = 9.64, P = 0.002; F1,115.76 = 66.23, P = 0.008,
	respectively;

Table VI .1

 VI Results of the linear mixed models testing the effect of species and sex on response (body morphology, chela strength, growth rate, behavior, and metabolism) and effect trait (excretion, elemental composition, trophic position, consumption rate and bioturbation) traits. Significant P values are in bold. σ 2 Round corresponds to the variance between rounds of the experiment (intercept), and σ 2Residual corresponds to the variance within rounds (residual).

			2
	Response variable	Morphology	Explanatory variable 0	F	Df Df.res	Pr(>F)		σ 2	Round	σ 2	Residual
	Body Morphology	-2	species Female Male	116.182 1 115.82 <2.2e-16 *** Female Male	0.003	0.797
				sex	30.835 Sex	1 115.92 1.81e-07 ***
	Chela strength			species	2.2455	1 115.71	0.13673		0.324	6.988
				sex	6.7404	1 115.41	0.01065	*
	Growth rate			species sex	2.7631 0.0227	1 115.94 1 115.61	0.09916 0.88044	.	0.037	1.684
	Behavior			species	9.6417	1 115.31 0.002394	**	0.159	1.026
				sex	0.4465	1 115.16 0.505320
	Metabolism			species	66.2964 1 115.76	5.016e-13	***	0.034	0.845
				sex	3.5324	1 115.44	0.0627	.
	Elemental composition			species	95.7099 1 115.45	<2.00E-16	***	0.000	1.244
				sex	6.5835	1 115.98	0.01157	*
	Excretion			species	82.5427 1 115.74	3.346e-15	***	0.042	0.959
				sex	0.4355	1 115.43	0.5106
	Trophic position			species	23.4342 1 115.45	4.042e-06	***	0.000	0.156
				sex	0.4214	1 115.98	0.5175
	Consumption rate			species	0.2369	1 115.45	0.6274			0	1.346
				sex	0.7521	1 115.98	0.3876
	Bioturbation			species sex	1.4102 0.3580	1 116.00 1 115.74 0.5508 0.2374		0.047	3.633

  , P < 0.001, respectively; Table1). Specifically, P. clarkii contained a higher C:N ratio, and lower N:P and C:P ratios than F. limosus (Figure VI.1; Figure VI.S3b). Additionally, NH4 + and PO4 3-excretion rates were higher for F. limosus than for P. clarkii (Figure VI.1; Figure VI.S3b). F. limosus displayed higher trophic position than P. clarkii (mean = 6.73 ± 0.05 SE and mean = 6.36 ± 0.06 SE for F. limosus and P. clarkii, respectively; Figure VI.1). Finally, the consumption rate and bioturbation did not differ between the two species (Table VI.1; Figure VI.1).

Table VI

 VI

	effect syndrome included bioturbation only (Figure VI.2). The response syndrome was
	positively associated with the effect syndrome (path coefficient = 0.68, CI95% = [0.52; 0.81], R 2
	= 0.35; Figure VI.2b).
	.3). Overall, F. limosus and P. clarkii displayed contrasted patterns of covariations in
	both response and effect traits. Specifically, the comparisons of the null and the
	unconstrained models showed that covariations among response and effect traits
	significantly differed between species (χ 2 = 45.73, P < 0.001 and χ 2 = 27.45, P = 0.002 for
	response and effect trait covariations, respectively; Table VI.S1).

Table VI .

 VI S1 (a) Covariance matrix of response traits for Procambarus clarkii and Faxonius limosus and (b) covariance matrix of effect traits for Procambarus clarkii and Faxonius limosus. Significant covariations are displayed in bold. Abundances of Procambarus clarkii (red) and Faxonius limosus (dark yellow) in lake Lamartine, calculated using catch per unit effort (CPUE) expressed in ind. trap -1 .hr -1 , on 9 occasions from June to December 2018. 36 baited traps (one cylindrical trap: 62cm x 34cm x 34cm, mesh size: 10 mm; one rectangular trap: 95cm x 20cm x 20cm, mesh size: 4 mm) were placed along transect lines, for one night (16h), and covered both littoral and pelagic habitats.

	(b) Figure VI.S1
	Species			Covariances		Estimate	Std.Err	z-value P(>|z|)
	P. clarkii	Elemental composition	Excretion		-0,112		0,05	-2,236	0,025
		Elemental composition	Trophic position	-0,101		0,092	-1,097	0,272
		Elemental composition	Consumption		-0,416		0,111	-3,741	0
		Elemental composition	Bioturbation		-0,376		0,114	-3,286	0,001
	(a)
	Species	Excretion	Covariances	Estimate Trophic position 0,095	Std.Err 0,068	z-value 1,39	P(>|z|) 0,165
	P. clarkii	Morphology Excretion		Chela strength Consumption	-0,023	0,345	0,082	0,085	-0,278 4,073	0,781 0
		Morphology Excretion		Growth rate Bioturbation	-0,035	0,162	0,073	0,08	-0,476 2,028	0,634 0,043
		Morphology		Behavior	-0,077		0,095		-0,806	0,42
		Morphology Trophic position	Metabolism Consumption	-0,079	0,041	0,049	0,138	-1,628 0,296	0,104 0,768
		Trophic position		Bioturbation		0,005		0,146	0,035	0,972
		Chela strength	Growth rate	-0,135		0,091		-1,495	0,135
		Chela strength Consumption	Behavior Bioturbation	-0,084	0,606	0,116	0,175	-0,73 3,465	0,466 0,001
	F. limosus	Chela strength Elemental composition Metabolism Excretion	-0,031	-0,056	0,058	0,093	-0,543 -0,606	0,587 0,544
		Elemental composition	Trophic position	-0,193		0,081	-2,391	0,017
		Growth rate Elemental composition Behavior Consumption	0,09	-0,069	0,103	0,084	0,872 -0,824	0,383 0,41
		Growth rate Elemental composition Metabolism Bioturbation	-0,071	-0,03	0,052	0,078	-1,354 -0,382	0,176 0,702
		Behavior Excretion		Metabolism Trophic position 0,213	0,086	0,072	0,094	2,962 0,92	0,003 0,358
		Excretion			Consumption		0,052		0,101	0,517	0,605
	F. limosus	Morphology Excretion		Chela strength Bioturbation	-0,256	0,099	0,118	0,095	-2,161 1,046	0,031 0,295
		Morphology		Growth rate	0,168		0,107		1,57	0,116
		Morphology Trophic position	Behavior Consumption	-0,009	0,063	0,079	0,084	-0,116 0,743	0,908 0,458
		Morphology Trophic position	Metabolism Bioturbation	0,079	-0,089	0,09	0,079	0,88 -1,125	0,379 0,26
		Chela strength Consumption	Growth rate Bioturbation	-0,341	-0,13	0,194	0,087	-1,753 -1,502	0,08 0,133
		Chela strength	Behavior	0,048		0,143		0,333	0,739
		Chela strength	Metabolism	-0,164		0,162		-1,011	0,312
		Growth rate		Behavior	-0,194		0,134		-1,447	0,148
		Growth rate		Metabolism	0,701		0,173		4,058	0
		Behavior		Metabolism	0,097		0,113		0,862	0,389

comprendre les conséquences fonctionnelles de la variabilité intraspécifique Les traits physiologiques au coeur du fonctionnement de l'écosystème

  Ce travail de thèse a mis en évidence l'existence d'une forte variabilité intraspécifique au sein de deux espèces invasives aux histoires d'invasion différentes, et a montré que les déterminants de cette variabilité étaient différents entre les deux espèces. Globalement, la variabilité génétique de F. limosus était plus faible et moins structurée spatialement que celle de P. clarkii (Chapitre III). Pour les deux espèces, la variabilité phénotypique (morphologique, trophique et stoechiométrique) était très importante au sein, mais également entre, les populations (Chapitres IV, V, VI). Nous avons identifié le rôle notable du type de gestion des écosystèmes dans la dissémination des deux espèces et leur structuration génétique mais celui-ci était extrêmement contexte-dépendant (e.g. introduction délibérée ou non intentionnelle ; Chapitre III). La variabilité phénotypique interpopulationnelle était surtout façonnée par des processus adaptatifs chez F. limosus, présente depuis plus longtemps dans le site d'étude, tandis qu'une part plus importante de processus neutres ainsi que l'histoire d'invasion expliquaient la variabilité des traits morphologiques et stoechiométriques chez P.

	Mieux De nombreuses études ont montré l'importance d'étudier les traits morphologiques des
	organismes (e.g. masse ou taille corporelle, Hildrew et al., 2007) puisqu'ils traduisent à la fois
	l'adaptation des organismes à leur environnement et leur rôle écologique (e.g. tant le type
	que l'intensité des processus impactés ; Woodward et al., 2005). En particulier, la masse
	corporelle est souvent associée aux variations de consommation de ressources (taux et types
	de ressources consommées ; Woodward & Hildrew, 2002; Reuman & Cohen, 2005). Nos
	travaux ont permis de mettre en évidence une forte variabilité morphologique indépendante
	de la masse résultant d'une adaptation locale entre les populations des deux espèces
	Globalement, ce travail de thèse souligne l'importance de considérer conjointement la
	variabilité génétique et la variabilité phénotypique au niveau intraspécifique, de façon à mieux
	comprendre les processus façonnant la biodiversité ainsi que les effets des organismes sur
	le fonctionnement des écosystèmes. Ceci est d'intérêt majeur dans le contexte des invasions
	biologiques qui perturbent les dynamiques des communautés et le fonctionnement des
	écosystèmes.

clarkii (Chapitres IV). Pour les deux espèces, les traits trophiques étaient très fortement dépendants des ressources disponibles dans les lacs. Au niveau intrapopulationnel, nous avons montré qu'une forte différenciation morphologique pouvait être associée à des différences d'utilisation des ressources trophiques entre les individus des habitats littoral et pélagique chez P. clarkii (Chapitre V). Nous avons également mis en évidence de fortes différences de syndrome fonctionnel entre les deux espèces dans un écosystème où elles coexistent (Chapitre VI). Ces résultats suggèrent que des individus d'espèces différentes mais aussi d'une même espèce pourraient impacter différemment les chaines trophiques des habitats littoral et pélagique, et le fonctionnement de l'écosystème dans son ensemble. invasives, mais également au sein de populations de P. clarkii entre individus occupant les habitats littoral et pélagique (Chapitres IV, V, VI). Cela suggère que les variations de forme de corps sont toutes aussi importantes à considérer que les variations de masse corporelle en général, puisqu'elles semblent mieux traduire la fonction écologique des individus dans l'écosystème

  . Les résultats des travaux présentés ici vont également dans ce sens Nous avons également montré que les impacts des organismes peuvent être prévisibles par l'étude des traits de réponse dans certaines populations invasives en raison de l'existence d'un fort syndrome fonctionnel (P. clarkii) tandis que d'autres sont plus cryptiques compte tenu d'un faible syndrome fonctionnel (F. limosus ; Chapitre VI). Plusieurs études ayant souligné la forte contexte-dépendance des covariations de traits[START_REF] Peiman | Comparative analyses of phenotypic trait covariation within and among populations[END_REF] Raffard et al., 2019[START_REF] Raffard | Does range expansion modify trait covariation? A study of a northward expanding dragonfly[END_REF], il serait intéressant d'étendre cette étude à plusieurs populations afin de (i) déterminer si le patron que nous avons observé est généralisable à d'autres populations pour chacune des deux espèces, et (ii) dans quelle mesure le degré de coexistence des deux espèces détermine la structure de covariations de traits[START_REF] Závorka | Co-existence with non-native brook trout breaks down the integration of phenotypic traits in brown trout parr[END_REF]. Nous avons vu que les traits physiologiques (stoechiométrie et métabolisme) semblent contraindre les covariations de traits chez les deux espèces étudiées (Chapitre VI ;Raffard et al., 2017). Il est intuitif de penser que les traits physiologiques peuvent affecter directement les processus écosystémiques tels que les flux de nutriments, la production primaire, ou encore la décomposition de la matière organique. Pourtant, la stoechiométrie, par exemple,

	puisque nous avons ont montré l'importance des traits stoechiométriques et
	comportementaux (P. clarkii) ainsi que métaboliques (P. clarkii et F. limosus) dans le syndrome
	fonctionnel, alors que les différences morphologiques (masse et forme de corps) n'étaient
	pas associées de manière significative au syndrome fonctionnel des deux espèces (Chapitre
	VI). Nous avons mesuré d'importantes variations stoechiométriques chez les deux espèces
	d'écrevisses en intra-et interpopulations (Chapitres IV, VI). Ceci supporte l'idée que les

impacts entre individus peuvent être très variés au sein des espèces invasives, par exemple à travers des variations d'excrétion de nutriments induisant des différences dans les cycles biogéochimiques

[START_REF] Vanni | Predicting nutrient excretion of aquatic animals with metabolic ecology and ecological stoichiometry: a global synthesis[END_REF]

. reste relativement peu intégrée dans les approches fonctionnelles multi-traits permettant de comprendre les mécanismes sous-jacents des effets sur les processus écosystémiques ou les structures de communauté (e.g. des covariations entre les compositions élémentaires, l'assimilation ou l'excrétion de nutriments, pourraient impacter la biodisponibilité des nutriments, la productivité ou encore le métabolisme de l'écosystème ;

[START_REF] Welti | Bridging food webs, ecosystem metabolism, and biogeochemistry using ecological stoichiometry theory[END_REF] mais voir Diaz Pauli et al., 2020 pour un effet sur les communautés d'invertébrés)

. Une meilleure compréhension des impacts des variations stoechiométrique (à la fois en intensité et direction) sur le fonctionnement de l'écosystème permettrait d'appréhender correctement les futurs impacts des espèces invasives dans le contexte de changement global, notamment dans les milieux dulçaquicoles où certains éléments comme le phosphore sont limitants et contraignent donc les processus écosystémiques.

Les dynamiques éco-évolutives traduisent les relations réciproques entre les processus écologiques et les processus évolutifs, aussi appelées boucles de rétroaction éco-évolutives. Elles correspondent à l'effet de l'évolution des individus sur la population, la communauté et l'écosystème mais aussi à l'effet de l'environnement qui modifie en retour l'évolution des individus(Hendry, 2016).

Remerciements

Acknowledgements

We are very grateful to R. Lassus, J. Salanon, R. M. Everts, C. Mulatero, M. Hautier, L. Riem-Galliano, X. Chevillot and A. Euphrasie for their help on the field. This work has been founded by the AEAG ("Agence de l'Eau Adour Garonne", DISPERSINVA project), by the CNRS-EC2CO (STOECHIOINVA project) and by the OFB ("Office Française de la Biodiversité", ERADINVA project).

Acknowledgements

We are grateful to the gravière team, particularly to Rémy Lassus, Paul Millet, Julien Salanon, Camille Mulatero, Gary Williams, Jérémy Fraysse, Bastien Jorigné and Thibault Pivetta, for their help during the fieldwork. We also thank Charlotte Veyssière and Héloïse Bossuat for her precious help in the laboratory. This work was supported by the OFB (Office Français pour la Biodiversité) as part of the ERADINVA project and by CNRS as part of the EC2CO project STOECHIOINVA. IL was supported by a PhD grant ATP from the University Toulouse III-Paul Sabatier.

Acknowledgements

We are grateful to the gravière team and our numerous colleagues for their help during the fieldwork and lake owners for access to the gravel pit lakes. We also thank two anonymous reviewers for their constructive comments that greatly improved the quality of this manuscript.

All sampling was performed under the authorization "Arrêté Préfectoral -08/08/2014". Financial support was provided by AFB (Agence Française pour la Biodiversité) as part of the ISOLAC and ERADINVA projects. IL is supported by a PhD grant ATP from the University Toulouse III -Paul Sabatier and CE by the Research Council of Norway through the Frimebdio program (project number 214189/F20).

Acknowledgements

We are grateful to Paul Millet, Gary Williams, Camille Mulatero, and Thibault Pivetta for their help during the fieldwork. We particularly thank Stéphanie Boulêtreau for her help during the setting up of the experimentation. This work was supported by the OFB (Office Français pour la Biodiversité) as part of the ERADINVA project and by CNRS as part of the EC2CO project STOECHIOINVA. IL was supported by a PhD grant ATP from the University Toulouse III-Paul Sabatier.

Acknowledgements

This work was funded by the ERAD-INVA project (ONEMA-AFB).

Supplementary material

Appendix

Appendix III.1 Genotyping quality controls A preliminary check of the overall levels of genetic diversity of F. limosus at the locus scale revealed that one locus (PCSH0042) was monomorphic for all populations and it was removed from subsequent analyses. We detected significant homozygote excesses for 10 locus/population pairs out of 144 possible pairs, although no clear intra-populational or intralocus pattern was detected. Significant linkage disequilibrium was detected for 1 out of 504 locus per locus per population combinations, and significant deviations from HW (after FDR correction) were only detected for 3 out of 144 locus/population pairs. Neutrality tests performed with Bayescan did not identify any outlier locus (Figure Appendix III.1-1).

For P. clarkii, we detected significant homozygote excesses for 27 locus/population pairs out of 602 possible combinations: loci PCLG48, PCSH0089, PCSH0005, PCLG15 and PCLG48 were involved in one pair each one; PCSH0006 was involved in two pairs, PCLG17, PCLG32, PCL29 and PCLG28 were involved in three pairs; and PCLG27 was involved in nine pairs. Given the moderate propensity of significant homozygote excesses (indicative of null alleles presence) observed for PCLG27 across populations (i.e. in 9/43 populations), it was removed for further analyses. We found one significant deviation from HW (after FDR correction) for all 597 locus/population pairs. Neither locus nor population was removed from the database following this analysis. We further detected significant linkage disequilibria between 141 out of 3,913 locus per locus per population combinations. Many of these significant disequilibria implied three specific populations (TAD, LAF, and VRA, with 62/91, 35/91 and 16/91 significant disequilibria respectively), accumulating 80% of all significant disequilibria, suggesting that the linkage disequilibria we detected for P. clarkii were mainly related to population-specific processes rather than to locus-specific problems. Neither locus nor population was therefore removed from the database following this analysis. Neutrality tests performed with Bayescan identified an outlier locus (PCSH0089) displaying significant negative q values at the 95% confidence level . Negative q values are indicative of purifying or balancing selection. We then removed this locus from the genetic database for subsequent analyses.

Supplementary information

Appendix

Appendix IV.A1 Genotyping, quality control Concerning P. clarkii, the average observed heterozygosity (Hobs) across sites ranged from 0.45 to 0.73, and the expected heterozygosity (Hexp) ranged from 0.43 to 0.71 (Appendix Table S1). We found significant homozygote excesses for only 15 out of 308 locus/populations pairs, significant HW deviations for 4 out of 308 locus/populations pairs, and significant linkage disequilibria for 2 out of 2002 within-population locus/locus combinations. No loci were removed following these analyses. Concerning neutrality tests, we detected one outlier locus (PCSH0089) that was probably affected by balancing or purifying selection (negative alpha) [START_REF] Foll | BayeScan v2.1[END_REF]. We removed this locus from subsequent analyses. The allelic richness (AR) ranged from 2.82 to 4.58 (see all genetic summary statistics in Appendix Table S1).

Concerning F. limosus, locus PCSH0042 was monomorphic in all populations and was removed for subsequent analyses. Hobs ranged from 0.04 to 0.21 while Hexp ranged from 0.06 to 0.20 (Appendix Table S1). We found significant homozygote excesses for only 4 out of 96 locus/populations pairs, no significant HW deviations and no linkage disequilibrium. AR varied from 1.21 to 2.16 (see all genetic summary statistics in Appendix Table S1).

Stable resource polymorphism along the benthic littoralpelagic axis in an invasive crayfish

Iris Lang, Charlotte Evangelista, Rebecca Everts, Géraldine Loot, Julien Cucherousset Adapted from an article published in Ecology and Evolution

Abstract

Although intraspecific variability is now widely recognized as affecting evolutionary and ecological processes, our knowledge on the importance of intraspecific variability within invasive species is still limited. This is despite the fact that understanding the linkage between within-population morphological divergences and the use of different trophic or spatial resources (i.e. resource polymorphism) can help to better predict their ecological impacts on recipient ecosystems. Here, we quantified the extent of resource polymorphism within populations of a worldwide invasive crayfish species, Procambarus clarkii, in 16 lake populations by comparing their trophic (estimated using stable isotope analyses) and morphological characteristics between individuals from the littoral and pelagic habitats. Our results first demonstrated that crayfish occur in both littoral and pelagic habitats of 7 lakes and that the use of pelagic habitat was associated with increased abundance of littoral crayfish. We then found morphological (i.e. body and chelae shapes) and trophic divergence (i.e. reliance on littoral carbon) among individuals from littoral and pelagic habitats, highlighting the existence of resource polymorphism in invasive populations. There was no genetic differentiation between individuals from the two habitats, implying that this resource polymorphism was stable (i.e. high gene flow between individuals). Finally, we demonstrated that a divergent adaptive process was responsible for the morphological divergence in body and chela shapes between habitats while difference in origin of the resource use neutrally evolved under genetic drift. These findings demonstrated that invasive P. clarkii can display strong within-population phenotypic variability in recent populations, and this could lead to contrasted ecological impacts between littoral and pelagic individuals. resource use). Finally, we quantified genetic differentiation between individuals from the littoral and pelagic habitats to determine the stability of resource polymorphism and its underlying mechanisms (i.e. adaptive or non-adaptive processes). We predicted that gene flow would be high (i.e. associated with stable polymorphism, [START_REF] Smith | Evolutionary significance of resource polymorphisms in fishes, amphibians, and birds[END_REF] in these recently colonized ecosystems, and that phenotypic variability would be mainly caused by an adaptive response to environmental conditions.

Material & methods

Study system and model species

The study was conducted in 16 gravel pit lakes ranging from 0.7 ha to 27.1 ha and located along the Garonne River in southwestern France [START_REF] Alp | Phenological response of a key ecosystem function to biological invasion[END_REF]Jackson et al., 2017) (Table Appendix V.1). Created between 1963 and 2007, these lakes are characterized by different environmental conditions arising from various levels of maturity and management practices [START_REF] Zhao | Environmental determinants of fish community structure in gravel pit lakes[END_REF]. Native from Northern America, P. clarkii is one of the most invasive crayfish species worldwide [START_REF] Oficialdegui | Unravelling the global invasion routes of a worldwide invader, the red swamp crayfish (Procambarus clarkii)[END_REF]. The species was introduced to France in 1976 and its presence in the studied area was first documented in 1995 [START_REF] Changeux | Évolution de la répartition des écrevisses en France Métropolitaine selon les enquêtes nationales mensées par le conseil supérieur de la pêche de 1977 à 2001[END_REF], indicating that the colonization process is relatively recent in those lakes. In the study area, P. clarkii are usually observed very rapidly once the lakes are created. Consequently, we assumed that lakes created before 1995 were colonized by P. clarkii in 1995, and that the lakes created afterwards were colonized during the first year of their creation (Table Appendix V.1). P. clarkii is known to induce strong negative impacts on native organisms and ecosystem processes due to predation, high competitiveness, disease transmission and ecological engineering [START_REF] Gherardi | Invasive crayfish in Europe: the impact of Procambarus clarkii on the littoral community of a Mediterranean lake[END_REF]Jackson et al., 2014). Chelae are important organs involved in multiple ecological functions of crayfish (e.g. predator-prey and competitor interactions, feeding behaviour, biological engineering; Gherardi et al., 2000;[START_REF] Matsuzaki | Contrasting impacts of invasive engineers on freshwater ecosystems: an experiment and meta-analysis[END_REF] which are known to display intraspecific morphological variations [START_REF] Claussen | Pinching forces in crayfish and fiddler crabs, and comparisons with the closing forces of other animals[END_REF][START_REF] Malavé | Size, shape, and sex-dependent variation in force production by crayfish chelae[END_REF]. In the studied system, previous investigations have revealed the existence of intraspecific variability among P. clarkii populations in terms of body morphology (Evangelista et al., 2019a), trophic ecology [START_REF] Jackson | Between-lake variation in the trophic ecology of an invasive crayfish[END_REF] and ecosystem impacts [START_REF] Alp | Phenological response of a key ecosystem function to biological invasion[END_REF]Evangelista et al., 2019b), as well as the presence of within-population phenotypic variability (Raffard et al., 2017).

Sampling and environmental characteristics

P. clarkii were sampled in the littoral and pelagic habitats of each lake. The littoral habitat was shallow (< 3 m) and characterized by a high level of structural heterogeneity. The nearshore substrate was composed of a mixture of gravels and cobbles with vegetation debris (e.g. downed trees, branches, helophytes) which provided sheltering opportunities for crayfish to hide against predators. The pelagic habitat was deeper and structurally more homogeneous.

The substrate was soft and exclusively composed of mud. Importantly, these lakes are not stratified.

Sampling was performed from mid-September to mid-October 2014 in the two habitats of each lake using pairs of baited traps (one cylindrical trap: 62cm x 34cm x 34cm, mesh size: 10 mm; one rectangular trap: 95cm x 20cm x 20cm, mesh size: 4 mm) set overnight (nlittoral = 4.0 traps ± 0.0 SD; npelagic = 3.9 ± 0.5 SD) and during the day (nlittoral = 6.0 ± 0.0 SD; npelagic = 4.9 ± 2.4 SD). Littoral traps were located within the first 5 meters along the shoreline in a shallow part (depth mean = 1.44 m ± 0.28 SD). Pelagic traps were located in the central (mean distance to shoreline = 71.01 m ± 26.57 SD) and profundal (depth mean = 3.59 m ± 1.24 SD) part of each lake (Table Appendix V.1). In each lake, we aimed at collecting 20 individuals from each habitat to capture intraspecific variability in the studied phenotypic traits (e.g. [START_REF] Weese | Contemporary and historical evolutionary processes interact to shape patterns of within-lake phenotypic divergences in polyphenic pumpkinseed sunfish, Lepomis gibbosus[END_REF][START_REF] Faulks | Genetic and morphological divergence along the littoral-pelagic axis in two common and sympatric fishes : perch, Perca fluviatilis (Percidae) and roach, Rutilus rutilus (Cyprinidae)[END_REF][START_REF] Lostrom | Linking stream ecology with morphological variability in a native freshwater fish from semi-arid Australia[END_REF]. When required, additional trapping in both habitats and hand netting along the shoreline (not feasible in the pelagic habitat) were performed to capture the targeted number of individuals. Crayfish were sexed, measured for carapace length (± 0.01 mm) and placed on ice for anesthesia. A small sample of muscle from the abdomen was subsequently collected on each specimen, stored in RNAlater© and frozen at the laboratory (-20°C) until subsequent genetic analyses. After collecting muscle tissue, each individual was placed in a labeled plastic bag and frozen in the laboratory. After defrosting, a sample of abdominal muscle was collected on each specimen, rinsed with distilled water and oven dried (60°C for 48 h) for stable isotope analyses.

On the same day as crayfish sampling, putative trophic resources of P. clarkii were collected in three different locations in each habitat of each lake to capture potential spatial heterogeneity in their stable isotope values. Specifically, periphyton and leaf litter were collected from the littoral, as they represent important components of P. clarkii's diet [START_REF] Alp | Phenological response of a key ecosystem function to biological invasion[END_REF][START_REF] Jackson | Between-lake variation in the trophic ecology of an invasive crayfish[END_REF], while pelagic zooplankton was collected using a 200-µm mesh net as we assume that pelagic individuals on muddy bottoms could consume detritus including zooplankton debris [START_REF] Smart | Feeding of the exotic Louisiana red swamp crayfish, Procambarus clarkii (Crustacea, Decapoda), in an African tropical lake : Lake Naivasha, Kenya[END_REF][START_REF] Ruokonen | Invasive crayfish increase habitat connectivity: a case study in a large boreal lake[END_REF]. Periphyton and omnivorous, as observed previously in the studied ecosystems [START_REF] Jackson | Between-lake variation in the trophic ecology of an invasive crayfish[END_REF]. This omnivorous diet was likely composed of a mixture of primary producers, invertebrates and fish (eggs and larvae or carrion) in both habitats [START_REF] Gutiérrez-Yurrita | Diet of the red swamp crayfish Procambarus clarkii in natural ecosystems of the Doñana National Park temporary fresh-water marsh (Spain)[END_REF]. Although it remains to be quantified, these results suggest that, in each habitat, P. clarkii display an opportunistic foraging strategy with a diet being primarily driven by resource availability rather than a form of trophic specialization that varies between habitats.

Phenotypic differentiation between littoral and pelagic individuals was not associated with genetic differentiation, highlighting the existence of non-assortative mating. The absence of significant genetic differentiation might be due to the recent colonization of lakes by P. clarkii (< 60 years, recent population bottleneck event; Dlugosch & Parker, 2008) and/or low reproductive isolation due to the relatively small size of the studied lakes (mean ± SE = 13.90 ± 1.78 ha). Thus, our results demonstrate that, within each lake, P. clarkii display a stable resource polymorphism with high gene flow between morphs and form a unique population [START_REF] Smith | Evolutionary significance of resource polymorphisms in fishes, amphibians, and birds[END_REF]. However, the temporal dynamic of this resource polymorphism remains to be quantified because gene flow between morphs could be reduced (e.g. philopatry behavior, breeding temporal segregation, emerging differences in mate choice), thus increasing the genetic differentiation along the littoral-pelagic gradient [START_REF] Meyer | Ecological and evolutionary consequences of the trophic polymorphism in Cichlasoma citrinellum (Pisces : Cichlidae)[END_REF]. In general, littoral-pelagic divergences observed in fish species are explained by combination of both phenotypic plasticity and genetic differences [START_REF] Smith | Evolutionary significance of resource polymorphisms in fishes, amphibians, and birds[END_REF][START_REF] Komiya | A novel resource polymorphism in fish, driven by differential bottom environments: an example from an ancient lake in Japan[END_REF][START_REF] Faulks | Genetic and morphological divergence along the littoral-pelagic axis in two common and sympatric fishes : perch, Perca fluviatilis (Percidae) and roach, Rutilus rutilus (Cyprinidae)[END_REF]. Here, trophic differentiation was not different from what was expected under the drift hypothesis (Pst < Fst), but Pst value for morphology was significantly higher than the Fst. Thus, adaptive process could explain the divergence of morphology, but this needs further investigations. Therefore, future studies should explore the relative importance of selection vs. phenotypic plasticity in driving phenotypic variation within invasive species.

In conclusion, we showed that stable resource polymorphism occurred between littoral and pelagic individuals of a recent biological invasion [START_REF] Smith | Evolutionary significance of resource polymorphisms in fishes, amphibians, and birds[END_REF]. The establishment of resource polymorphism within invasive populations can have important ecological and evolutionary implications, such as leading to different ecological impacts on the littoral and pelagic food chains [START_REF] Vander Zanden | Fishes as integrators of benthic and pelagic food webs in lakes[END_REF][START_REF] Ruokonen | Invasive crayfish increase habitat connectivity: a case study in a large boreal lake[END_REF].

Ecosystem impacts of invasive crayfish can vary among their populations (Evangelista et al., 2019b), and the present study suggests that they could also depend on within-population characteristics.

Appendix

Table Appendix V.1 Environmental characteristics of the 16 sampled lakes (Haute-Garonne, France). Resource polymorphism was studied in 7 lakes (highlighted in bold) where sufficient number of Procambarus clarkii were collected in both habitats (mean number of individuals per habitat = 19.79 ± 0.8 SD). Distance pelagic traps was assessed by measuring the distance (in meters) perpendicularly to the shore with GIS (accuracy of GPS ± 5m). Predation pressure was not assessed in lake O this year. * P. clarkii was present in the lake and collected using complementary sampling methods but not were sampled in the traps.

Lake

Contrasting functional trait covariations in two coexisting invasive crayfish species

Iris Lang, Allan Raffard, Benoît Pongérard, Julien Cucherousset

In preparation

Abstract

While the importance of intraspecific variability on evolutionary and ecological processes is now widely recognized, knowledge on the structure of response and effect trait variations and covariations (i.e. functional syndromes) is needed to understand the intrinsic links between the functions of organisms and their effect on ecosystem functioning. This is particularly important in the context of biological invasions because it can enhance our ability to predict the impacts of invasive species on recipient ecosystems. Using an experimental and multitrait approach, we compared the structure of response and effect traits variations and covariations of two co-occurring invasive crayfish, Procambarus clarkii and Faxonius limosus.

Overall, we demonstrated the existence of a high level of trait variability among individuals within invasive populations and between species. We also demonstrated that the two species displayed contrasting response and effect syndromes that were correlated to form different functional syndromes. Globally, P. clarkii displayed stronger trait covariations. These findings highlighted the contrasting functional relations of coexisting F. limosus and P. clarkii individuals, indicating that they had sharply distinct impacts on ecosystem functioning. More importantly, our understanding and ability to predict these impacts can be highly variable between species.

Functional syndromes

Regarding P. clarkii, the latent variable related with the response syndrome was positively and significantly associated with behavior (activity and anxiety-like behavior) and metabolism. The

Supplementary information

Libor Závorka Energy production presents a complex resource management challenge, given its association with habitat degradation, public-health impacts, and greenhouse-gas emissions. Energy production may now also be the largest driver of land-use change in the US, with biofuels -as well as mining and drilling for fossil fuels -having the heaviest footprints (Trainor et al. 2016).

Standing out in this energy landscape is the dedicated and potentially unique collaboration among stakeholders in the scientific community, conservation organizations, wildlife management agencies, and the wind industry. This collaboration began as wind energy expanded in the US from the early 1990s onward; first led to multi-stakeholder groups, such as the National Wind Coordinating Collaborative Wildlife Workgroup (www. nationalwind.org); and continued to expand and deepen over time. For example, in 2003, when a wind project in West Virginia was associated with large numbers of bat fatalities, it became apparent that research was needed to understand bat interactions with wind turbines. Bat Conservation International and stakeholders from the wind industry, scientific community, and government agencies subsequently created the Bats and Wind Energy Cooperative (BWEC; www. batsandwind.org). As a result, wind industry companies offered operational Genetic and phenotypic variability within two invasive species: patterns, determinants and consequences on freshwater ecosystem functioning.

Abstract

Intraspecific variability is now recognized for its importance on ecosystem functioning. In the context of biological invasions, which can strongly impact ecological processes, it is of high importance to understand the determinants and the patterns of genetic and phenotypic variability to fully apprehend the consequences of invasive individuals on recipient ecosystems. We demonstrated a high variability among and within populations of two crayfish species, Procambarus clarkii and Faxonius limosus, with distinct life-history traits and colonization histories in a narrow-invaded area. We highlighted that colonization history and environmental conditions were the main drivers of the contrasting patterns of genetic and phenotypic variability between the two species. Genetic analyses provided a great inference of local invasion pathways for P. clarkii, which had a great genetic variability, compared to F. limosus for which the local invasion pathways were more cryptic. We found that neutral and adaptive processes shaped the phenotypic variability of the two species in differing proportions. Then, we demonstrated the existence of a stable resource polymorphism along the benthic littoral-pelagic axis within populations of P. clarkii, suggesting that invaders could have contrasting impacts on ecosystem functioning between littoral and pelagic trophic chains. Finally, in an experiment context using a multi-traits approach, we demonstrated that the structure of trait covariations differed between species in a sympatric population, suggesting that P. clarkii impacts would be more predictable than F. limosus, and that P. clarkii could affect a higher range of ecological processes or impact the ecosystem functioning with a greater intensity than F. limosus. Overall, our findings stress the need to integrate intraspecific variability in the context of biological invasions to better understand their impacts on ecosystem functioning.

Variabilité génétique et phénotypique de deux espèces invasives