Patterns of split sex ratio in ants have multiple evolutionary causes based on different within-colony conflicts.

Split sex ratio-a pattern where colonies within a population specialize in either male or queen production-is a widespread phenomenon in ants and other social Hymenoptera. It has often been attributed to variation in colony kin structure, which affects the degree of queen-worker conflict over optimal sex allocation. However, recent findings suggest that split sex ratio is a more diverse phenomenon, which can evolve for multiple reasons. Here, we provide an overview of the main conditions favouring split sex ratio. We show that each split sex-ratio type arises due to a different combination of factors determining colony kin structure, queen or worker control over sex ratio and the type of conflict between colony members.

A fast Bayesian reconstruction algorithm for emission tomography with entropy prior converging to feasible images

The development and tests of an iterative reconstruction algorithm for emission tomography based on Bayesian statistical concepts are described. The algorithm uses the entropy of the generated image as a prior distribution, can be accelerated by the choice of an exponent, and converges uniformly to feasible images by the choice of one adjustable parameter. A feasible image has been defined as one that is consistent with the initial data (i.e. it is an image that, if truly a source of radiation in a patient, could have generated the initial data by the Poisson process that governs radioactive disintegration). The fundamental ideas of Bayesian reconstruction are discussed, along with the use of an entropy prior with an adjustable contrast parameter, the use of likelihood with data increment parameters as conditional probability, and the development of the new fast maximum a posteriori with entropy (FMAPE) Algorithm by the successive substitution method. It is shown that in the maximum likelihood estimator (MLE) and FMAPE algorithms, the only correct choice of initial image for the iterative procedure in the absence of a priori knowledge about the image configuration is a uniform field.

Queen acceptance in a socially polymorphic ant

A central question in social evolution is what processes regulate the number of breeders in each social group. Here, we tested whether differences in the rate of acceptance of new queens by resident workers could be a proximate cause explaining the coexistence of single- and multiple-queen colonies in an ant population. We found that Formica selysi workers discriminated against foreign (non-nestmate) queens, which contributes to maintaining the genetic integrity of the social group essential to kin selection. All the young and newly mated foreign queens introduced into experimental groups of workers died within 48 h. In contrast, workers frequently accepted young newly mated nestmate queens. The survival of nestmate queens was not significantly lower in groups of workers originating from single- queen colonies than in groups of workers originating from multiple-queen colonies. Finally, virgin queens had significantly higher survival than mated queens. Together, these results show that the maintenance of single-queen and multiple-queen colonies in the same population is unlikely to be caused by strong differences between the two types of colonies in their rate of acceptance of new queens by workers. They also suggest that the discrimination of queens by resident workers restricts the dispersal of foreign queens among colonies, but not the acceptance of additional nestmate queens.

Time-lapse and probabilistic inversion strategies for plane-wave electromagnetic data.

L'utilisation efficace des systèmes géothermaux, la séquestration du CO2 pour limiter le changement climatique et la prévention de l'intrusion d'eau salée dans les aquifères costaux ne sont que quelques exemples qui démontrent notre besoin en technologies nouvelles pour suivre l'évolution des processus souterrains à partir de la surface. Un défi majeur est d'assurer la caractérisation et l'optimisation des performances de ces technologies à différentes échelles spatiales et temporelles. Les méthodes électromagnétiques (EM) d'ondes planes sont sensibles à la conductivité électrique du sous-sol et, par conséquent, à la conductivité électrique des fluides saturant la roche, à la présence de fractures connectées, à la température et aux matériaux géologiques. Ces méthodes sont régies par des équations valides sur de larges gammes de fréquences, permettant détudier de manières analogues des processus allant de quelques mètres sous la surface jusqu'à plusieurs kilomètres de profondeur. Néanmoins, ces méthodes sont soumises à une perte de résolution avec la profondeur à cause des propriétés diffusives du champ électromagnétique. Pour cette raison, l'estimation des modèles du sous-sol par ces méthodes doit prendre en compte des informations a priori afin de contraindre les modèles autant que possible et de permettre la quantification des incertitudes de ces modèles de façon appropriée. Dans la présente thèse, je développe des approches permettant la caractérisation statique et dynamique du sous-sol à l'aide d'ondes EM planes. Dans une première partie, je présente une approche déterministe permettant de réaliser des inversions répétées dans le temps (time-lapse) de données d'ondes EM planes en deux dimensions. Cette stratégie est basée sur l'incorporation dans l'algorithme d'informations a priori en fonction des changements du modèle de conductivité électrique attendus. Ceci est réalisé en intégrant une régularisation stochastique et des contraintes flexibles par rapport à la gamme des changements attendus en utilisant les multiplicateurs de Lagrange. J'utilise des normes différentes de la norme l2 pour contraindre la structure du modèle et obtenir des transitions abruptes entre les régions du model qui subissent des changements dans le temps et celles qui n'en subissent pas. Aussi, j'incorpore une stratégie afin d'éliminer les erreurs systématiques de données time-lapse. Ce travail a mis en évidence l'amélioration de la caractérisation des changements temporels par rapport aux approches classiques qui réalisent des inversions indépendantes à chaque pas de temps et comparent les modèles. Dans la seconde partie de cette thèse, j'adopte un formalisme bayésien et je teste la possibilité de quantifier les incertitudes sur les paramètres du modèle dans l'inversion d'ondes EM planes. Pour ce faire, je présente une stratégie d'inversion probabiliste basée sur des pixels à deux dimensions pour des inversions de données d'ondes EM planes et de tomographies de résistivité électrique (ERT) séparées et jointes. Je compare les incertitudes des paramètres du modèle en considérant différents types d'information a priori sur la structure du modèle et différentes fonctions de vraisemblance pour décrire les erreurs sur les données. Les résultats indiquent que la régularisation du modèle est nécessaire lorsqu'on a à faire à un large nombre de paramètres car cela permet d'accélérer la convergence des chaînes et d'obtenir des modèles plus réalistes. Cependent, ces contraintes mènent à des incertitudes d'estimations plus faibles, ce qui implique des distributions a posteriori qui ne contiennent pas le vrai modèledans les régions ou` la méthode présente une sensibilité limitée. Cette situation peut être améliorée en combinant des méthodes d'ondes EM planes avec d'autres méthodes complémentaires telles que l'ERT. De plus, je montre que le poids de régularisation des paramètres et l'écart-type des erreurs sur les données peuvent être retrouvés par une inversion probabiliste. Finalement, j'évalue la possibilité de caractériser une distribution tridimensionnelle d'un panache de traceur salin injecté dans le sous-sol en réalisant une inversion probabiliste time-lapse tridimensionnelle d'ondes EM planes. Etant donné que les inversions probabilistes sont très coûteuses en temps de calcul lorsque l'espace des paramètres présente une grande dimension, je propose une stratégie de réduction du modèle ou` les coefficients de décomposition des moments de Legendre du panache de traceur injecté ainsi que sa position sont estimés. Pour ce faire, un modèle de résistivité de base est nécessaire. Il peut être obtenu avant l'expérience time-lapse. Un test synthétique montre que la méthodologie marche bien quand le modèle de résistivité de base est caractérisé correctement. Cette méthodologie est aussi appliquée à un test de trac¸age par injection d'une solution saline et d'acides réalisé dans un système géothermal en Australie, puis comparée à une inversion time-lapse tridimensionnelle réalisée selon une approche déterministe. L'inversion probabiliste permet de mieux contraindre le panache du traceur salin gr^ace à la grande quantité d'informations a priori incluse dans l'algorithme. Néanmoins, les changements de conductivités nécessaires pour expliquer les changements observés dans les données sont plus grands que ce qu'expliquent notre connaissance actuelle des phénomenès physiques. Ce problème peut être lié à la qualité limitée du modèle de résistivité de base utilisé, indiquant ainsi que des efforts plus grands devront être fournis dans le futur pour obtenir des modèles de base de bonne qualité avant de réaliser des expériences dynamiques. Les études décrites dans cette thèse montrent que les méthodes d'ondes EM planes sont très utiles pour caractériser et suivre les variations temporelles du sous-sol sur de larges échelles. Les présentes approches améliorent l'évaluation des modèles obtenus, autant en termes d'incorporation d'informations a priori, qu'en termes de quantification d'incertitudes a posteriori. De plus, les stratégies développées peuvent être appliquées à d'autres méthodes géophysiques, et offrent une grande flexibilité pour l'incorporation d'informations additionnelles lorsqu'elles sont disponibles. -- The efficient use of geothermal systems, the sequestration of CO2 to mitigate climate change, and the prevention of seawater intrusion in coastal aquifers are only some examples that demonstrate the need for novel technologies to monitor subsurface processes from the surface. A main challenge is to assure optimal performance of such technologies at different temporal and spatial scales. Plane-wave electromagnetic (EM) methods are sensitive to subsurface electrical conductivity and consequently to fluid conductivity, fracture connectivity, temperature, and rock mineralogy. These methods have governing equations that are the same over a large range of frequencies, thus allowing to study in an analogous manner processes on scales ranging from few meters close to the surface down to several hundreds of kilometers depth. Unfortunately, they suffer from a significant resolution loss with depth due to the diffusive nature of the electromagnetic fields. Therefore, estimations of subsurface models that use these methods should incorporate a priori information to better constrain the models, and provide appropriate measures of model uncertainty. During my thesis, I have developed approaches to improve the static and dynamic characterization of the subsurface with plane-wave EM methods. In the first part of this thesis, I present a two-dimensional deterministic approach to perform time-lapse inversion of plane-wave EM data. The strategy is based on the incorporation of prior information into the inversion algorithm regarding the expected temporal changes in electrical conductivity. This is done by incorporating a flexible stochastic regularization and constraints regarding the expected ranges of the changes by using Lagrange multipliers. I use non-l2 norms to penalize the model update in order to obtain sharp transitions between regions that experience temporal changes and regions that do not. I also incorporate a time-lapse differencing strategy to remove systematic errors in the time-lapse inversion. This work presents improvements in the characterization of temporal changes with respect to the classical approach of performing separate inversions and computing differences between the models. In the second part of this thesis, I adopt a Bayesian framework and use Markov chain Monte Carlo (MCMC) simulations to quantify model parameter uncertainty in plane-wave EM inversion. For this purpose, I present a two-dimensional pixel-based probabilistic inversion strategy for separate and joint inversions of plane-wave EM and electrical resistivity tomography (ERT) data. I compare the uncertainties of the model parameters when considering different types of prior information on the model structure and different likelihood functions to describe the data errors. The results indicate that model regularization is necessary when dealing with a large number of model parameters because it helps to accelerate the convergence of the chains and leads to more realistic models. These constraints also lead to smaller uncertainty estimates, which imply posterior distributions that do not include the true underlying model in regions where the method has limited sensitivity. This situation can be improved by combining planewave EM methods with complimentary geophysical methods such as ERT. In addition, I show that an appropriate regularization weight and the standard deviation of the data errors can be retrieved by the MCMC inversion. Finally, I evaluate the possibility of characterizing the three-dimensional distribution of an injected water plume by performing three-dimensional time-lapse MCMC inversion of planewave EM data. Since MCMC inversion involves a significant computational burden in high parameter dimensions, I propose a model reduction strategy where the coefficients of a Legendre moment decomposition of the injected water plume and its location are estimated. For this purpose, a base resistivity model is needed which is obtained prior to the time-lapse experiment. A synthetic test shows that the methodology works well when the base resistivity model is correctly characterized. The methodology is also applied to an injection experiment performed in a geothermal system in Australia, and compared to a three-dimensional time-lapse inversion performed within a deterministic framework. The MCMC inversion better constrains the water plumes due to the larger amount of prior information that is included in the algorithm. The conductivity changes needed to explain the time-lapse data are much larger than what is physically possible based on present day understandings. This issue may be related to the base resistivity model used, therefore indicating that more efforts should be given to obtain high-quality base models prior to dynamic experiments. The studies described herein give clear evidence that plane-wave EM methods are useful to characterize and monitor the subsurface at a wide range of scales. The presented approaches contribute to an improved appraisal of the obtained models, both in terms of the incorporation of prior information in the algorithms and the posterior uncertainty quantification. In addition, the developed strategies can be applied to other geophysical methods, and offer great flexibility to incorporate additional information when available.

Patterns of positive selection in seven ant genomes.

The evolution of ants is marked by remarkable adaptations that allowed the development of very complex social systems. To identify how ant-specific adaptations are associated with patterns of molecular evolution, we searched for signs of positive selection on amino-acid changes in proteins. We identified 24 functional categories of genes which were enriched for positively selected genes in the ant lineage. We also reanalyzed genome-wide data sets in bees and flies with the same methodology to check whether positive selection was specific to ants or also present in other insects. Notably, genes implicated in immunity were enriched for positively selected genes in the three lineages, ruling out the hypothesis that the evolution of hygienic behaviors in social insects caused a major relaxation of selective pressure on immune genes. Our scan also indicated that genes implicated in neurogenesis and olfaction started to undergo increased positive selection before the evolution of sociality in Hymenoptera. Finally, the comparison between these three lineages allowed us to pinpoint molecular evolution patterns that were specific to the ant lineage. In particular, there was ant-specific recurrent positive selection on genes with mitochondrial functions, suggesting that mitochondrial activity was improved during the evolution of this lineage. This might have been an important step toward the evolution of extreme lifespan that is a hallmark of ants.

Variation in the level of aggression, chemical and genetic distance among three supercolonies of the Argentine ant in Europe.

In their invasive ranges, Argentine ant populations often form one geographically vast supercolony, genetically and chemically uniform within which there is no intraspecific aggression. Here we present regional patterns of intraspecific aggression, cuticular hydrocarbons (CHCs) and population genetics of 18 nesting sites across Corsica and the French mainland. Aggression tests confirm the presence of a third European supercolony, the Corsican supercolony, which exhibits moderate to high levels of aggression, depending on nesting sites, with the Main supercolony, and invariably high levels of aggression with the Catalonian supercolony. The chemical analyses corroborated the behavioural data, with workers of the Corsican supercolony showing moderate differences in CHCs compared to workers of the European Main supercolony and strong differences compared to workers of the Catalonian supercolony. Interestingly, there were also clear genetic differences between workers of the Catalonian supercolony and the two other supercolonies at both nuclear and mitochondrial markers, but only very weak genetic differentiation between nesting sites of the Corsican and Main supercolonies (F(ST) = 0.06). A detailed comparison of the genetic composition of supercolonies also revealed that, if one of the last two supercolonies derived from the other, it is the Main supercolony that derived from the Corsican supercolony rather than the reverse. Overall, these findings highlight the importance of conducting more qualitative and quantitative analyses of the level of aggression between supercolonies, which has to be correlated with genetic and chemical data.

Characterization and distribution of Pogonomyrmex harvester ant lineages with genetic caste determination.

Genetic caste determination has been described in two populations of Pogonomyrmex harvester ants, each comprising a pair of interbreeding lineages. Queens mate with males of their own and of the alternate lineage and produce two types of diploid offspring, those fertilized by males of the queens' lineage which develop into queens and those fertilized by males of the other lineage which develop into workers. Each of the lineages has been shown to be itself of hybrid origin between the species Pogonomyrmex barbatus and Pogonomyrmex rugosus, which both have typical, environmentally determined caste differentiation. In a large scale genetic survey across 35 sites in Arizona, New Mexico and Texas, we found that genetic caste determination associated with pairs of interbreeding lineages occurred frequently (in 26 out of the 35 sites). Overall, we identified eight lineages with genetic caste determination that always co-occurred in the same complementary lineage pairs. Three of the four lineage pairs appear to have a common origin while their relationship with the fourth remains unclear. The level of genetic differentiation among these eight lineages was significantly higher than the differentiation between P. rugosus and P. barbatus, which questions the appropriate taxonomic status of these genetic lineages. In addition to being genetically isolated from one another, all lineages with genetic caste determination were genetically distinct from P. rugosus and P. barbatus, even when colonies of interbreeding lineages co-occurred with colonies of either putative parent at the same site. Such nearly complete reproductive isolation between the lineages and the species with environmental caste determination might prevent the genetic caste determination system to be swept away by gene flow.

Ecology and evolution of social-organization: insights from fire ants and other highly eusocial insects

Social organisms exhibit conspicuous intraspecific variation in all facets of their social organization. A prominent example of such variation in the highly eusocial Hymenoptera is differences in the number of reproductive queens per colony, Differences in queen number in ants are associated with differences in a host of reproductive and social traits, including queen phenotype and breeding strategy, mode of colony reproduction, and pattern of sex allocation. We examine the causes and consequences of changes in colony queen number and associated traits using the fire ant Solenopsis invicta as a principal model. Ecological constraints on mode of colony founding may act as important selective forces causing the evolution of queen number in this and many other ants, with social organization generally perpetuated across generations by means of the social environment molding appropriate queen phenotypes and reproductive strategies. Shifts in colony queen number have profound effects on genetic structure within nests and may also influence genetic structure at higher levels (aggregations of nests or local demes) because of the association of queen number with particular mating and dispersal habits. Divergence of breeding habits between populations with different social organizations has the potential to promote genetic differentiation between these social variants. Thus, evolution of social organization can be important in generating intrinsic selective regimes that channel subsequent social evolution and in initiating the development of significant population genetic structure, including barriers to gene flow important in cladogenesis.

Numerical algorithm for Ginzburg-Landau equations with multiplicative noise: Application to domain growth

We consider stochastic partial differential equations with multiplicative noise. We derive an algorithm for the computer simulation of these equations. The algorithm is applied to study domain growth of a model with a conserved order parameter. The numerical results corroborate previous analytical predictions obtained by linear analysis.

Majorization arrow in quantum-algorithm design

We apply majorization theory to study the quantum algorithms known so far and find that there is a majorization principle underlying the way they operate. Grover's algorithm is a neat instance of this principle where majorization works step by step until the optimal target state is found. Extensions of this situation are also found in algorithms based in quantum adiabatic evolution and the family of quantum phase-estimation algorithms, including Shor's algorithm. We state that in quantum algorithms the time arrow is a majorization arrow.

Granulocyte-macrophage colony-stimulating factor elicits bone marrow-derived cells that promote efficient colonic mucosal healing.

BACKGROUND: Granulocyte-macrophage colony-stimulating factor (GM-CSF) therapy is effective in treating some Crohn's disease (CD) patients and protects mice from colitis induced by dextran sulfate sodium (DSS) administration. However, its mechanisms of action remain elusive. We hypothesized that GM-CSF affects intestinal mucosal repair. METHODS: DSS colitic mice were treated with daily pegylated GM-CSF or saline and clinical, histological, and inflammatory parameters were kinetically evaluated. Further, the role of bone marrow-derived cells in the impact of GM-CSF therapy on DSS colitis was addressed using cell transfers. RESULTS: GM-CSF therapy reduced clinical signs of colitis and the release of inflammatory mediators. GM-CSF therapy improved mucosal repair, with faster ulcer reepithelialization, accelerated hyperproliferative response of epithelial cells in ulcer-adjacent crypts, and lower colonoscopic ulceration scores in GM-CSF-administered mice relative to untreated mice. We observed that GM-CSF-induced promotion of mucosal repair is timely associated with a reduction in neutrophil numbers and increased accumulation of CD11b(+) monocytic cells in colon tissues. Importantly, transfer of splenic GM-CSF-induced CD11b(+) myeloid cells into DSS-exposed mice improved colitis, and lethally irradiated GM-CSF receptor-deficient mice reconstituted with wildtype bone marrow cells were protected from DSS-induced colitis upon GM-CSF therapy. Lastly, GM-CSF-induced CD11b(+) myeloid cells were shown to promote in vitro wound repair. CONCLUSIONS: Our study shows that GM-CSF-dependent stimulation of bone marrow-derived cells during DSS-induced colitis accelerates colonic tissue repair. These data provide a putative mechanism for the observed beneficial effects of GM-CSF therapy in Crohn's disease.