Les algues non-indigènes ont des impacts sur les communautés naturelles à une échelle mondiale: elles affectent la biodiversité et le fonctionnement des écosystèmes ainsi que les services écosystémiques, avec des conséquences économiques et sociales. Parmi les conséquences de ces introductions sont le déplacement d'espèces indigènes, des compétitions avec des espèces en danger et des effets sur les trajectoires éco-évolutives des espèces des communautés envahies. Bien que crucial pour anticiper le devenir des espèces non-indigènes, comprendre les mécanismes d'acclimatation et d'adaptation agissant post-introduction reste un challenge chez les algues. Au cours de cette thèse, nous avons étudié certains processus d'acclimatation, en particulier le rôle des bactéries associées, et leurs effets, en utilisant comme modèle d'étude Sargassum muticum. Cette algue brune originaire d'Asie, est une espèce emblématique parmi les algues introduites avec une présence du Mexique à l'Alaska en Amérique et du Maroc à la Norvège en Europe. Nous avons effectué une analyse bibliographique des traits et caractéristiques écologiques qui pourraient expliquer son succès. Nous avons ensuite montré que l'acidification n'a pas d'effets significatifs sur les bacteries associées, bien que des changements saisonniers du microbiome aient été observés. Enfin, nous avons utilisé un modèle de niche écologique, intégrant la phénologie, pour prédire la distribution de S. muticum sous deux scénarios de changement climatique. Selon nos résultats, d'ici 2100, la distribution de S. muticum devrait se déplacer vers le nord dans l'hémisphère nord avec des régressions dans certaines zones actuellement occupées. / Non-indigenous seaweeds impact natural communities worldwide, affecting biodiversity, ecosystem functioning, and ecosystem services, resulting in significant economic and social consequences. Among major impacts are the displacement of native species, a threat to endangered species, and effects on ecological and evolutionary processes within the invaded communities. While critical to predict the fate of introduced species, understanding the mechanisms of acclimation and adaptation following introduction represents a great challenge in seaweeds. In this thesis, we investigated some acclimation processes, with an emphasis on the role of associated microbiota, and examined their effects with Sargassum muticum as a model species. This brown seaweed native to Asia, is an emblematic invader among seaweeds, with a distribution now ranging from Mexico to Alaska in America and from Morocco to Norway in Europe. We first reviewed the competitive advantages and traits that may contribute to its invasiveness. We then showed that acidification has no significant effects on associated bacteria, although seasonal changes in the microbiome have been observed. Finally, we applied ecological niche modelling, but innovatively accounting for phenology, to project the distribution of S. muticum under two future climate change scenarios. According to our projections, by 2100 the distribution of S. muticum is expected to shift northwards along its European, North American and Asian distributions with partial retreat from the currently occupied areas.

Les modèles de niche écologique (ENM) sont largement utilisés pour prédire la distribution actuelle et future des espèces. Ils peuvent être des outils complémentaires pour évaluer la qualité de niche des potentielles aires de lâchers, un facteur clé pour le succès des translocations. Pourtant, les ENM sont encore rarement appliqués dans les translocations et on a encore peu de preuves de leur intérêt pour les translocations. Nous avons centré nos recherches sur des programmes bien établis de renforcement des populations de deux espèces d'Outarde houbara, l'espèce nord-africaine (Chlamydotis undulata) et l'espèce migratrice asiatique (C. macqueenii). Grâce à un suivi intensif de populations sauvages relictuelles et d'individus élevés en captivité et lâchés sur une large partie de leur aire de répartition, ces programmes fournissent un cadre d'étude idéal pour envisager des questions complexes sur la pertinence des ENM dans la translocation. Nous avons relié la survie individuelle, une composante essentielle de la dynamique des populations, à la qualité de niche, en réalisant notamment un lâcher expérimental de 180 individus le long du gradient de qualité de la niche. Nous avons ensuite testé si les outardes lâchées utilisent la même niche écologique que les sauvages pour valider l'utilisation ultérieure des projections des modèles. Enfin, nous discutons de l'implication des changements globaux pour les translocations d'Outarde houbara. Ces approches empiriques reliant la qualité de niche aux processus démographiques constituent un pas en avant pour une meilleure compréhension de la pertinence des ENM pour les translocations d'espèces dans un environnement changeant. / Ecological niche models (ENM) are widely used to predict the current and future distribution of species. They could be used as complementary tools to assess the niche suitability of potential release areas, a key parameter for improving success in conservation translocation. Yet, ENM are still rarely applied and general evidence about the benefit of these models in translocation is still lacking. We focused our research on reinforcement programs of two species of Houbara Bustard, the sedentary North African species (Chlamydotis undulata undulata) and the migratory Asian species (C. macqueenii). Through the extensive monitoring of remnant wild populations and captive-born released individuals over a large proportion of their distribution range, these programs provide an ideal study framework to address complex questions regarding the relevancy of ENM in translocation conservation. First, we linked individual survival, a crucial component of population dynamics, to niche suitability. Then, we performed an experimental release and monitoring of 180 individuals along a gradient of habitat suitability as predicted by ENM to test the effect of release site suitability on survival of captive-born individuals. We then tested if released houbaras use the same ecological niche than wild houbaras, as a validation step to support the subsequent use of niche modelling. Finally, we discussed the implications of global change for ongoing translocation programs of Houbara Bustard. Empirical approaches linking habitat suitability with demographic processes provide a step towards a better understanding of the relevance of ENM for conservation translocations in changing environments.

In most tropical river systems there has been a lack of integrated ecological research to investigate the dynamics and impacts of invasive species on recipient river systems. This is in sharp contrast to temperate river systems. This thesis investigated the nature, extent, and impact of Nile tilapia, Oreochromis niloticus (Linnaeus, 1758), on indigenous congenerics within the Limpopo River basin in northern South Africa. An integrated approach was adopted to gain a better understanding of factors that allow Nile tilapia to be a successful invader and also to gain an insight into its invasion rate and conservation implications within South Africa. Morphometric and genetic variation between Nile tilapia, indigenous congenerics and their associated hybrids were determined. Intermediate meristic characters obscured the identification of hybrid specimens from pure morpho-specimens and species identity was only confirmed through mtDNA analysis. Preliminary evidence points to unidirectional hybridization among Oreochromis congeners in the Limpopo River system. The hypothesis that bigger Nile tilapia males may have a competitive advantage over spawning grounds and in female mate choice is proposed. The trophic ecology of Nile tilapia was investigated using both stomach contents and stable isotope analysis. A high similarity in stomach contents was observed but interspecific differences were revealed in the isotopic composition of diets that suggest fine scale patterns of resource partitioning that could be achieved by the ability of fish to selectively feed on what is immediately available and the ability to perceive the dynamics that determine food resource availability. Ecological niche models were used to determine the potential invasive range of Nile tilapia and revealed broad invasive potential over most river systems in southern Africa that overlapped the natural range of endemic congenerics. It was noted that model performance and the degree of niche conservatism varied significantly with variable selection and spatial extent of study area. This implied that the spatial distribution of suitable and unsuitable environmental variables varied between the native and introduced ranges of Nile tilapia and also indicated the ability of Nile tilapia to survive in conditions incongruent with its native range. The extreme hardiness and adaptive life history characteristics of Nile tilapia have probably predisposed it to be a successful invader in novel systems within southern Africa. Lastly, a qualitative risk assessment method was developed as a potential application to determine the risk of establishment and spread of the invasive Nile tilapia. Results showed that in the absence of quantitative data on ecosystem structure and functioning, habitat suitability analysis in terms of known physiological tolerance limits to minimum water temperature, presence or absence of dams, seasonality of river flows and the presence of indigenous fish species of concern could be adequate for identifying vulnerable river systems. The model developed also provides an objective method that is easy to implement, modify and improve on as new data become available. Furthermore, the model can be applied to highlight areas of uncertainty where future research should be directed. / Thesis (PhD)--University of Pretoria, 2012. / Zoology and Entomology / Unrestricted

Climate change will likely have impacts on disease vector distribution. Posing a significant health threat in the 21st century, risk of tick-borne diseases may increase with higher annual mean temperatures and changes in precipitation. We modeled the current and future potential distribution of the Ixodes ricinus tick species in Europe. The Genetic Algorithm for Rule-set Prediction (GARP) was utilized to predict potential distributions of I. ricinus based on current (1990-2010 averages) and future (2040-2060 averages) environmental variables. A ten model best subset was created out of a possible 200 models based on omission and commission criteria. Our results show that under the A2 climate change scenario the potential habitat range for the I. ricinus tick in Europe will expand into higher elevations and latitudes (e.g., Scandinavia, the Baltics, and Belarus), while contracting in other areas (e.g., Alps, Pyrenees, interior Italy, and northwestern Poland). Overall, a potential habitat expansion of 3.8% in all of Europe is possible. Our results may be used to inform climate change adaptation efforts in Europe.

The genus Castor is represented in Eurasia by Castor fiber, North America by C. canadensis, and has been in North America since the late Miocene. This study aims to assess whether morphology of Miocene-Pliocene C. californicus and extant C. canadensis are distinctly different. Specimens of Castor were compared using geometric morphometrics on cranial material and linear measurements of postcranial material. Species occurrence data were compared with past and future climate data to assess Castor distribution in North America through time. Results show that C. canadensis is highly variable in both cranial and postcranial morphology and C. californicus falls largely within the range of variation seen within the extant species. Past distributions match fossil occurrences of Castor, suggesting confidence in projected models. Morphological and distribution similarities between the two species suggest that they can be treated as ecological analogs, though evaluation of whether they are conspecific will require more data.

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Spruce-Fir forests are relicts from the Pleistocene and can only be found within the Southern Appalachians. Analyzing the relationships between species distribution, climatic parameters, topography, and biotic interactions through ecological niche modeling creates prediction maps for conservation efforts. Maxent, Boosted Regression, and Random Forest were utilized to compare which model and variable combinations best approximate the unique mountain forest environment. Maxent with a bias file produced optimal results and was used to examine distributional changes that may occur in the future and how these changes compare to paleo-environmental distributions. Fraser fir has shown evidence of being influenced by changing climates based on historical data and in future predictions. These findings show areas of decline in 2050 and 2070. When combined with weather, climate, genetics, and ecological studies, this is a useful tool for resource allocation to areas that are predicted to be resilient in the face of climate change.

I compared the performance of habitat models created from data of differing reliability. Because the reliability is dependent on the probability of detecting the species, I experimented to estimate detectability for a salamander species. Based on these estimates, I investigated the sensitivity of habitat models to varying detectability. Models were created using a database of amphibian and reptile observations at Fort A.P. Hill, Virginia, USA. Performance was compared among modeling methods, taxa, life histories, and sample sizes. Model performance was poor for all methods and species, except for the carpenter frog (Rana virgatipes). Discriminant function analysis and ecological niche factor analysis (ENFA) predicted presence better than logistic regression and Bayesian logistic regression models. Database collections of observations have limited value as input for modeling because of the lack of absence data. Without knowledge of detectability, it is unknown whether non-detection represents absence. To estimate detectability, I experimented with red-backed salamanders (Plethodon cinereus) using daytime, cover-object searches and nighttime, visual surveys. Salamanders were maintained in enclosures (n = 124) assigned to four treatments, daytime__low density, daytime__high density, nighttime__low density, and nighttime__high density. Multiple observations of each enclosure were made. Detectability was higher using daytime, cover-object searches (64%) than nighttime, visual surveys (20%). Detection was also higher in high-density (49%) versus low-density enclosures (35%). Because of variation in detectability, I tested model sensitivity to the probability of detection. A simulated distribution was created using functions relating habitat suitability to environmental variables from a landscape. Surveys were replicated by randomly selecting locations (n = 50, 100, 200, or 500) and determining whether the species was observed, based on the probability of detection (p = 40%, 60%, 80%, or 100%). Bayesian logistic regression and ENFA models were created for each sample. When detection was 80 __ 100%, Bayesian predictions were more correlated with the known suitability and identified presence more accurately than ENFA. Probability of detection was variable among sampling methods and effort. Models created from presence/absence data were sensitive to the probability of detection in the input data. This stresses the importance of quantifying detectability and using presence-only modeling methods when detectability is low. If planning for sampling as an input for suitability modeling, it is important to choose sampling methods to ensure that detection is 80% or higher. / Ph. D.

Distributional ecology is a branch of ecology which aims to reconstruct and predict the geographic range of free-living and symbiotic organisms in terrestrial and aquatic ecosystems. More recently, distributional ecology has been used to map disease transmission risk. The implementation of distributional ecology for disease transmission has, however, been erroneous in many cases. The inaccurate representation of disease distribution is detrimental to effective control and prevention. Furthermore, ecological niche modeling experiments are generally developed and tested using data from terrestrial organisms, neglecting aquatic organisms in case studies. Both disease and aquatic systems are often data limited, and current modeling methods are often insufficient. There is, therefore, a need to develop data-driven models that perform accurately even when only limited amounts of data are available or when there is little to no knowledge of the species' natural history to be modeled. Here, I propose a data-driven ecological niche modeling method that requires presence-only data (i.e., absence, pseudoabsence, or background records are not needed for model calibration). My method is expected to reconstruct environmental conditions where data-limited aquatic organisms are more likely to be present, based on a density-based clustering algorithm as a proxy of the realized niche (i.e., abiotic, and biotic environmental conditions occupied by the organism). Supported by ecological theories and methods, my central hypothesis is that because density-based clustering machine-learning modeling prevents extrapolation and interpolation, it can robustly reconstruct the realized niche of a data-limited aquatic organism. First, I assembled a comprehensive dataset of abiotic (temperature) and biotic (phytoplankton) environmental conditions and presence reports using Vibrio cholerae, a well-understood aquatic bacterium species in coastal waters globally (Chapter 2). Second, using V. cholerae as a model system, I developed detailed parameterizations of density-based clustering models to determine the parameter values with the best capacities to reconstruct and predict the species' distribution in global seawaters (Chapter 3). Finally, I compared the performance of density-based clustering modeling against traditional, correlative machine-learning ecological niche modeling methods (Chapter 4). Density-based clustering models, when assessed based on model fit and prediction, had comparable performance to traditional 'data-hungry' machine-learning correlative methods used in modern applications of ecological niche modeling. Modeling the environmental and geographic ranges of V. cholerae, an aquatic organism of free-living and parasitic ecologies, is a novel approach itself in distributional ecology. Ecological niche modeling applications to pathogens, such as V. cholerae, provide an opportunity to further the knowledge of directly-transmitted emerging diseases for which only limited data are available. Density-based clustering ecological niche modeling is termed here as Marble, honoring a previous, experimental version of this analytical approach, and is expected to provide new opportunities to understand how an ecological niche modeling method influences estimates of the distribution of data-limited organisms of complex ecology. These are lessons applicable to novel, rare, and cryptic aquatic organisms, such as emerging diseases, endangered fishes, and elusive aquatic species. / Master of Science / Distributional ecology is a branch of ecology which aims to reconstruct and predict the geographic distribution of land and water organisms. In the case of diseases, a correct representation of their geographic distributions is key for successful management. Previous studies highlight the need to develop new models that perform accurately even when limited amounts of data are available and there is little to no knowledge of the organisms' ecology. This thesis proposes a data-driven method, originally termed Marble. Marble is expected to help reconstruct environmental conditions where data-limited aquatic organisms are more likely to be found. Supported by ecological theories and methods, my hypothesis is that because Marble prevents under- and over-fitting, this method will produce results which better fit the data. Using V. cholerae, an aquatic organism, as a model system, I compared the performance of Marble against other traditional modeling algorithms. I found that Marble, in terms of model fit, performed similarly to traditional methods used in distributional ecology. Modeling the ecology of V. cholerae is a new approach in and of itself in ecological modeling. Furthermore, modeling pathogens provides an opportunity to further the knowledge of directly transmitted diseases, and Marble is expected to provide opportunities to understand how algorithm selection can reconstruct (or not) the distribution of data-limited aquatic organisms of diverse ecologies.