ABSTRACT This thesis examines phylogenetic patterns in three New Zealand amphipod taxa in relation to current geographic distributions and historical climatic (e.g. glaciation, marine inundation) and geological (e.g. mountain building) events using DNA sequencing and distributional data. It also examines how recognition behaviour can be used to delineate potential species boundaries and to assess the role of sexual selection. The endemic genus Phreatogammarus has been found in only a limited number of sites and is not very abundant. An analysis of the genetic variation of two species within the genus using allozyme electrophoresis revealed high levels of genetic differentiation among populations but low levels within populations. This suggested that limited dispersal occurred among habitats with one population possibly representing a cryptic species. The endemic freshwater genus Paraleptamphopus is thought to contain a large number of undescribed species with a number of these existing in small waterbodies such as seepages. Examination of the phylogeographic patterns using both mtDNA (CO1) and nuclear DNA (28S) showed that a number of distinct genetic lineages exist, with CO1 revealing 21 haplotypes with genetic distance of over 20%. Using a molecular clock rate of 2.4%, most haplotypes diverged approximately 8-12 million years ago during the Miocene era, possibly as a result of greater land availability increasing habitat diversity or by allopatric speciation. Morphological and genetic differences were not congruent, with morphologically similar taxa appearing among highly genetically distinct lineages, and some morphologically distinct forms appearing within single lineages. The distribution and habitat variables of 419 sites were analysed to determine what was affecting the presence or absence of Paraleptamphopus. The presence of native vegetation in catchments had a positive affect on Paraleptamphopus distribution suggesting that large anthropogenic changes in catchment vegetation could have a negative effect on their abundance. I found smaller waterbodies to be more important than larger ones highlighting the need to study such sites as rare taxa may be ignored. A better understanding is needed on the role of small waterbodies in promoting overall species diversity in catchments. Examination of Paracalliope fluviatilis phylogenetic patterns using the mtDNA gene CO1 showed that a number of separate clades existed suggesting long term isolation and limited dispersal among catchments. Due to the large genetic divergences among some populations there was the possibility that cryptic species might exist. Species recognition experiments were conducted on seven populations to help determine whether cryptic species were present. For the three most genetically divergent crosses there was bias against inter-population pairings, suggesting that there were between two or three separate species. Using a combined field and laboratory approach, size assortative mating was examined in Paracalliope fluviatilis. The field study showed positive size assortative mating and that larger females carried more eggs, suggesting they were more fecund. A series of laboratory experiments examining four existing theories explaining the phenomenon found that none adequately explained positive size assortative mating in P. fluviatilis. I therefore presented two new explanations to explain size assortative mating: a combination of female resistance and size-related variation in a male's capacity to amplex larger females or a form of indirect intra-sexual competition.

Abstract Most models of sexual selection focus on coevolution of male sexual trait and female preference for the trait. However, whether the female preference modifies the male trait depends on the overall receptivity of females, on the importance of the male trait for the females, on female sampling behaviour, and on female control over copulation decision. These aspects are often neglected by theoreticians. Female receptivity, song requirement and preferences were studied in two Drosophila virilis group species, D. montana and D. virilis. The main object of the study was female acceptance/rejection behaviour. Female wing spreading posture was a signal for males to attempt copulation, when the female was ready to mate. I used this signal as an indicator of female acceptance. D. virilis females were generally very receptive, but there were differences between females both in receptivity and in responsiveness of the females to simulated courtship songs. D. virilis female did not require song and had a low acceptance threshold with a heterospecific male. These two traits are explained by a high female receptivity. D. montana females, on the contrary, had a high acceptance threshold. These females accepted the courting male only after hearing his song. They also repelled males, which attempted copulation without female acceptance signal. In this species the strength of species discrimination did not correlate with the overall receptivity of the females. Between species hybrid females (from a cross vir x mo and from backcross to mo) resembled D. montana females in their song requirement, but not in their receptivity. This suggests that these two traits are inherited independently. D. montana and D. littoralis females have previously been found to prefer males with short and dense sound pulses in wild. These song characters were repeatable among overwintered males in a fashion different from other song characters. This shows that song characters involved in sexual selection are more sensitive to environmental factors than other song traits.

The neotropical lizard genus Anolis is an important model system for studies of the ecology and evolution of animal diversity. One of the most striking elements of Anolis diversity is found in the morphology of the dewlap, an extensible flap of colored skin on the throat that anoles use to communicate during social interactions. The evolutionary forces that have promoted the evolution of dewlap diversity are poorly understood. A study of reproductive success in A. carolinensis showed for the first time that dewlap color is currently under selection in an anole (Chapter 1). However, this is unlikely to be a result of intrasexual competition because neither dewlap morphology nor reproductive success are related to male territory size or quality. Instead the dewlap may be under intersexual selection from female mate choice. In addition to sexual selection, the dewlap may evolve in response to a variety of other processes such as species recognition, predation, sensory drive, or a combination of these. A study of variation among populations of a single species, A. sagrei, revealed that the dewlap may be undergoing rapid adaptive diversification driven by several of these processes simultaneously (Chapter 2), while a study of variation among species in dewlap size showed that similar processes are likely shaping the evolution of the dewlap in female anoles (Chapter 3). In a case study of male-female pair formation in the Costa Rican anole A. limifrons, dewlap size or color were not good predictors of which males would form pairs and which would not, though males and females that were similar in size were found to form pairs more often than animals that were dissimilar in size (Chapter 4). Finally, a study of the correlated evolution of traits related to locomotion in anoles found that morphology, behavior, and habitat use evolve in tandem among 31 species of anoles from the Greater Antilles (Chapter 5). Together, these studies suggest that the evolutionary ecology of anoles is more complex than previously thought, and that future studies of the dewlap may provide more general insight into the evolution of diversity of animal ornaments.

The epidemiology of blastomycosis remains poorly understood in part due to the lack of a robust and discriminatory strain typing method for Blastomyces dermatitidis. Here we describe the development of a multilocus sequence (MLST) method to study the genetic variation and population structure of B. dermatitidis. Eighty geographically diverse clinical and environmental isolates were examined. Thirty-six unique sequence types were identified. With a discriminatory index of 91.4%, MLST identifies significant genetic diversity for the characterization of local and global B. dermatitidis isolates. To test whether this fungus represented a single species throughout its geographic range we performed phylogenetic analyses, applying Genealogical Concordance Phylogenetic Species Recognition (GCPSR). Phylogenetic analysis revealed two distinct clades, with five of the eight gene phylogenies studied supporting the separation of these lineages, which were also geographically partitioned. Based on fulfillment of GCPSR, we propose the current species B. dermatitidis harbors two genetically distinct non-interbreeding phylogenetic species.

The epidemiology of blastomycosis remains poorly understood in part due to the lack of a robust and discriminatory strain typing method for Blastomyces dermatitidis. Here we describe the development of a multilocus sequence (MLST) method to study the genetic variation and population structure of B. dermatitidis. Eighty geographically diverse clinical and environmental isolates were examined. Thirty-six unique sequence types were identified. With a discriminatory index of 91.4%, MLST identifies significant genetic diversity for the characterization of local and global B. dermatitidis isolates. To test whether this fungus represented a single species throughout its geographic range we performed phylogenetic analyses, applying Genealogical Concordance Phylogenetic Species Recognition (GCPSR). Phylogenetic analysis revealed two distinct clades, with five of the eight gene phylogenies studied supporting the separation of these lineages, which were also geographically partitioned. Based on fulfillment of GCPSR, we propose the current species B. dermatitidis harbors two genetically distinct non-interbreeding phylogenetic species.

No description available.

No description available.

L’objectif de ces travaux de thèse est la reconnaissance automatique des espèces d’arbres à partir de scans laser terrestres, information indispensable en inventaire forestier. Pour y répondre, nous proposons différentes méthodes de reconnaissance d’espèce basées sur la texture géométrique 3D des écorces.Ces différentes méthodes utilisent la séquence de traitement suivante : une étape de prétraitement, une étape de segmentation, une étape d’extraction des caractéristiques et une dernière étape de classification. Elles sont fondées sur les données 3D ou bien sur des images de profondeur extraites à partir des nuages de points 3D des troncs d’arbres en utilisant une surface de référence.Nous avons étudié et testé différentes approches de segmentation sur des images de profondeur représentant la texture géométrique de l'écorce. Ces approches posent des problèmes de sur-Segmentation et d'introduction de bruit. Pour cette raison, nous proposons une nouvelle approche de segmentation des nuages de points 3D : « Burst Wind Segmentation », inspirée des lignes de partage des eaux. Cette dernière réussit, dans la majorité des cas, à extraire des cicatrices caractéristiques qui sont ensuite comparées à un dictionnaire des cicatrices (« ScarBook ») pour discriminer les espèces d’arbres.Une grande variété de caractéristiques est extraite à partir des régions segmentées par les différentes méthodes proposées. Ces caractéristiques représentent le niveau de rugosité, la forme globale des régions segmentées, la saillance et la courbure du contour, la distribution des points de contour, la distribution de la forme selon différents angles,...Enfin, pour la classification des caractéristiques visuelles, les forêts aléatoires (Random Forest) de Leo Breiman et Adèle Cutler sont utilisées dans une approche à deux étapes : sélection des variables importantes, puis classification croisée avec les variables retenues, seulement.L’écorce de l’arbre change avec l'accroissement en diamètre ; nous avons donc étudié différents critères de variabilité naturelle et nous avons testé nos approches sur une base qui présente cette variabilité. Le taux de bonne classification dépasse 96% dans toutes les approches de segmentation proposées mais les meilleurs résultats sont atteints avec la nouvelle approche de segmentation « Burst Wind Segmentation » étant donné que cette approche réussit mieux à extraire les cicatrices, utilise un dictionnaire de cicatrices et a été évaluée sur une plus grande variété de caractéristiques de forme, de courbure, de saillance et de rugosité. / The objective of the thesis is the automatic recognition of tree species from Terrestrial LiDAR data. This information is essential for forest inventory. As an answer, we propose different recognition methods based on the 3D geometric texture of the bark.These methods use the following processing steps: a preprocessing step, a segmentation step, a feature extraction step and a final classification step. They are based on the 3D data or on depth images built from 3D point clouds of tree trunks using a reference surface.We have investigated and tested several segmentation approaches on depth images representing the geometric texture of the bark. These approaches have the disadvantages of over segmentation and are quite sensitive to noises. For this reason, we propose a new 3D point cloud segmentation approach inspired by the watershed technique that we have called «Burst Wind Segmentation». Our approach succeed in extracting in most cases the characteristic scars that are next compared to those stored in a dictionary («ScarBook») in order to determine the tree species.A large variety of characteristics is extracted from the regions segmented by the different methods proposed. These characteristics are the roughness, the global shape of the segmented regions, the saliency and the curvature of the contour, the distribution of the contour points, the distribution of the shape according to the different orientations.Finally, for the classification of the visual characteristics, the Random Forest method by Leo Breiman and Adèle Cutler is used in a two steps approach: selection of the most important variables and cross classification with the selected variables.The bark of the tree changes with the trunk diameter. We have thus studied different natural variability criteria and we have tested our approaches on a test set that includes this variability. The accuracy rate is over 96% for all the proposed segmentation approaches but the best result is obtained with the «Burst Wind Segmentation» one due to the fact that this approach can better extract the scars, it uses a dictionary of scars for recognition, and it has been evaluated on a greater variety of shapes, curvatures, saliency and roughness.

Diversas pesquisas focam no estudo e conservação das abelhas, em grande parte por sua importância para a agricultura. Entretanto, a identicação de espécies de abelhas vem sendo um impedimento para a condução de novas pesquisas, já que demanda tempo e um conhecimento muito especializado. Apesar de existirem diversos métodos para realizar esta tarefa, muitos deles são excessivamente custosos, restringindo sua aplicabilidade. Por serem facilmente acessíveis, as asas das abelhas vêm sendo amplamente utilizadas para a extração de características, já que é possível aplicar técnicas morfométricas utilizando apenas uma foto da asa. Como a medição manual de diversas características é tediosa e propensa a erros, sistemas foram desenvolvidos com este propósito. Entretanto, os sistemas ainda possuem limitações e não há um estudo voltado às técnicas de classificação que podem ser utilizadas para este m. Esta pesquisa visa avaliar as técnicas de extração de características e classificação de modo a determinar o conjunto de técnicas mais apropriado para a discriminação de espécies de abelhas. Nesta pesquisa foi demonstrado que o uso de uma conjunção de características morfométricas e fotométricas obtêm melhores resultados que o uso de somente características morfométricas. Também foram analisados os melhores algoritmos de classificação tanto usando somente características morfométricas, quanto usando uma conjunção de características morfométricas e fotométricas, os quais são, respectivamente, o Naïve Bayes e o classificador Logístico. Os Resultados desta pesquisa podem guiar o desenvolvimento de novos sistemas para identificação de espécies de abelha, objetivando auxiliar pesquisas conduzidas por biólogos. / Several researches focus on the study and conservation of bees, largely because of its importance for agriculture. However, the identification of bee species has hampering new studies, since it demands a very specialized knowledge and is time demanding. Although there are several methods to accomplish this task, many of them are excessively costly, restricting its applicability. For being accessible, the bee wings have been widely used for the extraction of features, since it is possible to apply morphometric techniques using just one image of the wing. As the manual measurement of various features is tedious and error prone, some systems have been developed for this purpose. However, these systems also have limitations, and there is no study concerning classification techniques that can be used for this purpose. This research aims to evaluate the feature extraction and classification techniques in order to determine the combination of more appropriate techniques for discriminating species of bees. The results of our research indicate that the use of a conjunction of Morphometric and Pixel-based features is more effective than only using Morphometric features. OuranalysisalsoconcludedthatthebestclassicationalgorithmsusingbothonlyMorphometric features and a conjunction of Morphometric and Pixel-based features are, respectively, Naïve Bayes and Logistic classier. The results of this research can guide the development of new systems to identify bee species in order to assist in researches conducted by biologists.

Diversas pesquisas focam no estudo e conservação das abelhas, em grande parte por sua importância para a agricultura. Entretanto, a identicação de espécies de abelhas vem sendo um impedimento para a condução de novas pesquisas, já que demanda tempo e um conhecimento muito especializado. Apesar de existirem diversos métodos para realizar esta tarefa, muitos deles são excessivamente custosos, restringindo sua aplicabilidade. Por serem facilmente acessíveis, as asas das abelhas vêm sendo amplamente utilizadas para a extração de características, já que é possível aplicar técnicas morfométricas utilizando apenas uma foto da asa. Como a medição manual de diversas características é tediosa e propensa a erros, sistemas foram desenvolvidos com este propósito. Entretanto, os sistemas ainda possuem limitações e não há um estudo voltado às técnicas de classificação que podem ser utilizadas para este m. Esta pesquisa visa avaliar as técnicas de extração de características e classificação de modo a determinar o conjunto de técnicas mais apropriado para a discriminação de espécies de abelhas. Nesta pesquisa foi demonstrado que o uso de uma conjunção de características morfométricas e fotométricas obtêm melhores resultados que o uso de somente características morfométricas. Também foram analisados os melhores algoritmos de classificação tanto usando somente características morfométricas, quanto usando uma conjunção de características morfométricas e fotométricas, os quais são, respectivamente, o Naïve Bayes e o classificador Logístico. Os Resultados desta pesquisa podem guiar o desenvolvimento de novos sistemas para identificação de espécies de abelha, objetivando auxiliar pesquisas conduzidas por biólogos. / Several researches focus on the study and conservation of bees, largely because of its importance for agriculture. However, the identification of bee species has hampering new studies, since it demands a very specialized knowledge and is time demanding. Although there are several methods to accomplish this task, many of them are excessively costly, restricting its applicability. For being accessible, the bee wings have been widely used for the extraction of features, since it is possible to apply morphometric techniques using just one image of the wing. As the manual measurement of various features is tedious and error prone, some systems have been developed for this purpose. However, these systems also have limitations, and there is no study concerning classification techniques that can be used for this purpose. This research aims to evaluate the feature extraction and classification techniques in order to determine the combination of more appropriate techniques for discriminating species of bees. The results of our research indicate that the use of a conjunction of Morphometric and Pixel-based features is more effective than only using Morphometric features. OuranalysisalsoconcludedthatthebestclassicationalgorithmsusingbothonlyMorphometric features and a conjunction of Morphometric and Pixel-based features are, respectively, Naïve Bayes and Logistic classier. The results of this research can guide the development of new systems to identify bee species in order to assist in researches conducted by biologists.