Feral swine (Sus scrofa) are an invasive species in the Mississippi Alluvial Valley (MAV). They cause millions in damage annually to agriculture, and likely negatively affect native wildlife species. Using camera traps, I monitored 36 forest patches within the MAV to assess the effects of swine invasions on native wildlife species richness. I also modified the double-observer point count technique into a new method for estimating swine abundance with camera traps. Feral swine suppressed native vertebrate richness by 26% when compared to uninvaded patches. I validated the new double-observer technique by determining if it could detect an abundance-area relationship in wildlife populations and estimate a known decrease in abundance following swine removal. This technique was sensitive enough to detect the increase and decrease in abundance and estimated the number of individuals removed from the population relatively accurately. This technique may be useful in the future to manage feral swine populations.

South Pacific humpback whales were devastated by commercial whaling in their Antarctic feeding areas during the 20th century. Understanding migratory connections and current abundance of these isolated breeding stocks is crucial for the allocation of historical Antarctic catches in population dynamic models used to assess current recovery. However, only a small number of migratory connections have been documented between Oceania breeding stocks within the South Pacific and feeding areas in the Antarctic. In addition, little is known about abundance of these stocks which encompass a vast oceanic region. For this thesis I first used mixed-stock analysis (MSA) to allocate migratory connections from four Antarctic feeding areas (n=142) to seven South Pacific breeding stocks (n=1,373), including four in Oceania, based on genetic marker frequencies. The use of this method was justified by the breeding stocks showing genetic differentiation at the haplotype level with an F[subscript ST] value of 0.027 (p-value <0.001). The results showed a relatively strong connection of Western Australia to Antarctic Area IV, Tonga to the border of Antarctic Area VI/I, Colombia to the Antarctic Peninsula, and a split allocation of Eastern Australia and New Caledonia to Antarctic Area V. This study provides the first population-level information supporting previous individual-based studies that humpback whale migration may not necessarily be direct north south. Next, utilizing capture-recapture methodology of unique humpback whale fluke photographs, I estimated abundance of one of the least studied Oceania breeding stocks, French Polynesia, a stock which also showed no significant migratory allocation using MSA. Taking into consideration the possible advantages of using Quality Control (QC) photographs to minimize bias in matching, estimates were generated using the complete photo catalogue and also using only photographs adhering to QC criteria. I found that the choice of using QC has an effect on the abundance generated and discuss the implications of this finding. Despite the photo catalogue used, the French Polynesia stock is estimated to number less than 1,900 individuals. Lastly, to provide additional information on the French Polynesia stock I used photo-identification to compare French Polynesia whales to whales in the Antarctic Peninsula and Strait of Magellan (Antarctic Area I), a possible migratory connection suggested by previous microsatellite genotyping. No conclusive matches were found. Although this does not discount the possibility of a few migrants traveling between these regions it does indicate the Antarctic Peninsula and the Strait of Magellan are not primary feeding areas of French Polynesia. This new information regarding abundance and migration of French Polynesia whales is important for the Comprehensive Assessment of Southern Hemisphere humpback whales. This document is currently being completed as the International Whaling Commission considers the next critical steps in recovery for Oceania humpback whales stocks. / Graduation date: 2010

La gestion durable des ressources naturelles vivantes est un problème majeur dans un contexte de raréfaction, dû à l'impact de l'homme et à une incertitude omniprésente. Améliorer les outils existant et en développer de nouveaux pour conseiller les gestionnaires sur l'évolution potentielle des ressources naturelles vivantes, selon divers scénarios environnementaux et de gestion, est nécessaire. Cette thèse a pour but de contribuer au développement d'une méthodologie pour l'aide à la décision pour la gestion des ressources naturelles vivantes, tout en prenant en compte les sources d'incertitude majeures. Ce travail est appliqué au cas de la population de saumon atlantique (Salmo salar L.) de la Nivelle (France). Cette population fait l'objet d'un programme de suivi à long terme et cette espèce a été largement étudiée. Cette dernière est menacée mais elle est toujours ciblée par la pêche commerciale et récréative. Elle illustre la dualité entre conservation et exploitation, qui est au coeur de la gestion des ressources naturelles vivantes. Pour gérer une population, il est nécessaire de comprendre sa dynamique et de prédire son évolution sous divers scénarios environnementaux et de gestion. L'approche Bayésienne fournit un cadre cohérent pour quantifier l'incertitude sous ses différentes formes. Les modèles hiérarchiques permettent l'assimilation de sources de données multiples et de faire des inférences et des prédictions sur des grandeurs spatio-temporelles inconnues. Un modèle stochastique d'état Bayésien, i.e. un modèle hiérarchique Bayésien dynamique, est construit pour étudier la dynamique de la population d'intérêt et pour prédire son évolution. La théorie de la décision en univers incertain fournit un cadre pour aider un individu dans ses choix, mais son application reste difficile. En théorie, une fonction d'utilité qui dépend des conséquences des alternatives de gestion reflète les préférences d'un individu unique impliqué dans un problème décisionnel. En pratique, sa construction est malaisée. Premièrement, il estdifficile de définir une valeur pour chaque conséquence. Deuxièmement, il y a généralement plus d'un individu impliqué dans le problème décisionnel. Par conséquent, on obtient une classe de fonctions d'utilité. De par les différents intérêts, souvent conflictuels, que les gestionnaires ont à prendre en compte, la fonction d'utilité est multi variée. Dans cette thèse, une classe de fonctions d'utilité bi-variées est construite. Elle prend en compte l'incertitude concernant la fonction, les variations de préférence entre les acteurs et la dualité d'intérêts exploitation vs conservation. Ensuite, une analyse de la robustesse est réalisée pour étudier si la décision optimale, i.e. l'utilité espérée maximale, varie lorsque la fonction d'utilité varie.La méthodologie développée dans cette thèse s'est avérée possible et fructueuse. Elle fournit un cadre cohérent pour organiser les interactions entre scientifiques, acteurs et gestionnaires pour atteindre une compréhension commune des problèmes de décision dans la gestion des ressources naturelles vivantes. En reconnaissant explicitement la diversité des acteurs, elle permet d'identifier des conflits potentiels et de guider les gestionnaires vers des compromis acceptables. Cependant, elle demande un haut niveau de formation et d'expertise en modélisation et en calcul. Elle implique également un temps d'analyse important. Comment rendre ces exigences compatibles avec le niveau actuel d'expertise et les agendas à court terme des structures de gestion est un challenge principal pour le futur. / The sustainable management of natural living resources is a major issue in a context of increasing scarcity due to human impact and of pervasive uncertainty. Improving existing tools and developing new ones to advise decision makers on the potential evolution of natural living resources, according to various management and environmental scenarios, is requested. This PhD aims at contributing to the development of a methodology for decision making for natural living resources management, while taking into account major sources of uncertainty. This is achieved through the study case of the Atlantic salmon (Salmo salar L.) population ofthe Nivelle River (France). This population is subjected to a long term monitoring program and the species has been extensively studied. Atlantic salmon is a threatened species but still targeted by commercial and recreational fisheries. It illustrates the duality between conservation and exploitation which is at the heart of natural living resource management. To manage a population, it is necessary to understand its dynamics and to predict its evolution under various management and environmental scenarios. The Bayesian approach provides a coherent framework to quantify uncertainty in its different forms. Hierarchical models allow the assimilation of multiple sources of data and to make spatio-temporal inferences and predictions. A Bayesian state space model, i.e. a Bayesian dynamic hierarchical model, is constructed to study the dynamics of the population of interest and topredict its evolution. The decision theory under uncertainty provides a framework to help an individual in its choices, but its application still raises difficulties. In theory, a utility function depending on the consequences of alternative actions reflects the preferences of a single individual involved in a decision problem. In practice, its construction is challenging. Firstly, it is difficult to assign a value for each consequence. Secondly, there is usually more than one individual involved in the decision problem. Consequently, we obtain a set of utility functions. Due to the various and often conflicting interests the decision maker has to take into account, the utility function is multivariate. In this PhD, a set of bivariate utility functions is constructed. It accounts for the uncertainty about the function, the variation of preferences among stakeholders and the dual interests of exploitation vs conservation. Next, a robustness analysis is performed to study if the optimal decision, i.e. associated to the maximum expected utility, varies when the utility function varies. The methodology developed in this PhD proved practicable and fruitful. It provides a coherent framework for organizing the interactions between scientists, stakeholders and decision makers for reaching a common understanding of decision problems in the management of natural living resources. By acknowledging explicitly the diversity among stakeholders, it allows to identify potential conflict and it helps guiding decision makers towards acceptable trade-off actions. However, it requires a high level of training and expertise in modelling and computation. It involves also thoughtful and time consuming analyses. How to render these requirements compatible with the current level of expertise and the short term agendas of management bodies is a main challenge for the near future.