Thesis (Ph. D.)--University of Washington, 1995. / Vita. Includes bibliographical references (leaves [75]-79).

Thesis (Ph. D.)--University of Hong Kong, 1995. / Includes bibliographical references (leaves 267-316).

Thesis (Ph. D.)--Ludwig-Maximilians-Universität München, 2005.. / Title from PDF title page (viewed on May 13, 2006). Includes three articles co-authored with Sebastian Diehl. Vita. Includes bibliographical references.

The Chabařovice coal mining pit is currently still under the process of continuous flooding and its area increased up to 174 ha since 2001.Adult perch (Perca fluviatilis) have been the most numerous fish of the lake until 2004. Fish were collected during the ichtyological survey sampling campaigns in June and September.Diet composition was expressed as percent weight, which was calculated for each prey taxon.

Bibliography: pages 163-183. / A generic, size-based simulation model is developed to investigate the dynamics of carbon and nitrogen flows in plankton communities. All parameters in the model are determined by body size using empirically-determined relationships calculated from published data. The model is robust with respect to most parameters and assumptions. Because the model is based on general ecological principles, it can be used to simulate microplankton community interactions in any planktonic ecosystem. Two coastal ecosystems from the southern Benguela region in South Africa are simulated; one typical of the relatively stable surface waters on the Agulhas Bank and one typical of upwelling plumes, usually found off the west coast of South Africa. Simulated communities compare well with field observations in terms of standing stocks and size composition, and simulation results indicate that the small-scale structure of the two ecosystems and the processes occurring within them are relatively well understood. Consequently, the dynamic functioning of the two systems is investigated at the ecosystem level, using the simulation results. Hypothetical carbon flow networks are constructed, and the average importance of different flow pathways at different times is assessed. In both ecosystems, the vast majority of carbon flows pass through short, efficient-transfer pathways, although longer pathways are potentially possible. Simulation analyses are extended from coastal to oceanic food webs, and the model results are consistent with the hypothesis that oceanic phytoplankton have rapid rates of primary production. At-sea sampling of a phytoplankton bloom is mimicked by "sampling" from simulation output, and interpretation of the data using standard techniques is compared with the model output. The dangers of extrapolating from snapshot measurements is highlighted, and the experiment emphasizes the importance of size-fractionated sampling of phytoplankton. A hypothetical pelagic food web is described, consisting of at least five different trophic pathways from phytoplankton to pelagic fish. It is suggested that coastal waters probably have all the different pathways, and the relative importance and efficiency of the different pathways will determine the total fish production in an ecosystem.

Seven small (3.2 to 5.2 m total length) whale sharks were observed suction feeding on patches of surface plankton in the Bay of La Paz within 1 km of shore and 2 km N of the phosphate dock at San Juan de la Costa, on 1-2 November 1993. The sharks were photographed and videotaped from the boat and by snorkelers in the water. When actively feeding the shark turned its head from side to side, part of the head was lifted out of the water, and the mouth opened and closed 7 to 28 times per minute (x̄ = 17, N = 13). These suction gulps were synchronized with the opening and closing of the gill slits. This feeding behavior occurred only in the patchy areas of densely cloudy water, a layer 10 to 30 cm thick at the surface containing an immense concentration of copepods, 95% of which were identified as Acartia clausi. Remoras accompanying the whale sharks also fed on the plankton bloom.

Plâncton são organismos microscópicos que constituem a base da cadeia alimentar de ecossistemas aquáticos. Eles têm importante papel no ciclo do carbono pois são os responsáveis pela absorção do carbono na superfície dos oceanos. Detectar, estimar e monitorar a distribuição das diferentes espécies são atividades importantes para se compreender o papel do plâncton e as consequências decorrentes de alterações em seu ambiente. Parte dos estudos deste tipo é baseada no uso de técnicas de imageamento de volumes de água. Devido à grande quantidade de imagens que são geradas, métodos computacionais para auxiliar no processo de análise das imagens estão sob demanda. Neste trabalho abordamos o problema de identificação da espécie. Adotamos o pipeline convencional que consiste dos passos de detecção de alvo, segmentação (delineação de contorno), extração de características, e classificação. Na primeira parte deste trabalho abordamos o problema de escolha de um algoritmo de segmentação adequado. Uma vez que a avaliação de resultados de segmentação é subjetiva e demorada, propomos um método para avaliar algoritmos de segmentação por meio da avaliação da classificação no final do pipeline. Experimentos com esse método mostraram que algoritmos de segmentação distintos podem ser adequados para a identificação de espécies de classes distintas. Portanto, na segunda parte do trabalho propomos um método de classificação que leva em consideração múltiplas segmentações. Especificamente, múltiplas segmentações são calculadas e classificadores são treinados individualmente para cada segmentação, os quais são então combinados para construir o classificador final. Resultados experimentais mostram que a acurácia obtida com a combinação de classificadores é superior em mais de 2% à acurácia obtida com classificadores usando uma segmentação fixa. Os métodos propostos podem ser úteis para a construção de sistemas de identificação de plâncton que sejam capazes de se ajustar rapidamente às mudanças nas características das imagens. / Plankton are microscopic organisms that constitute the basis of the food chain of aquatic ecosystems. They have an important role in the carbon cycle as they are responsible for the absorption of carbon in the ocean surfaces. Detecting, estimating and monitoring the distribution of plankton species are important activities for understanding the role of plankton and the consequences of changes in their environment. Part of these type of studies is based on the analysis of water volumes by means of imaging techniques. Due to the large quantity of generated images, computational methods for helping the process of image analysis are in demand. In this work we address the problem of species identification. We follow the conventional pipeline consisting of target detection, segmentation (contour delineation), feature extraction, and classification steps. In the first part of this work we address the problem of choosing an appropriate segmentation algorithm. Since evaluating segmentation results is a subjective and time consuming task, we propose a method to evaluate segmentation algorithms by evaluating the classification results at the end of the pipeline. Experiments with this method showed that distinct segmentation algorithms might be appropriate for identifying species of distinct classes. Therefore, in the second part of this work we propose a classification method that takes into consideration multiple segmentations. Specifically, multiple segmentations are computed and classifiers are trained individually for each segmentation, which are then combined to build the final classifier. Experimental results show that the accuracy obtained with the combined classifier is superior in more than 2% to the accuracy obtained with classifiers using a fixed segmentation. The proposed methods can be useful to build plankton identification systems that are able to quickly adjust to changes in the characteristics of the images.

Plâncton são organismos microscópicos que constituem a base da cadeia alimentar de ecossistemas aquáticos. Eles têm importante papel no ciclo do carbono pois são os responsáveis pela absorção do carbono na superfície dos oceanos. Detectar, estimar e monitorar a distribuição das diferentes espécies são atividades importantes para se compreender o papel do plâncton e as consequências decorrentes de alterações em seu ambiente. Parte dos estudos deste tipo é baseada no uso de técnicas de imageamento de volumes de água. Devido à grande quantidade de imagens que são geradas, métodos computacionais para auxiliar no processo de análise das imagens estão sob demanda. Neste trabalho abordamos o problema de identificação da espécie. Adotamos o pipeline convencional que consiste dos passos de detecção de alvo, segmentação (delineação de contorno), extração de características, e classificação. Na primeira parte deste trabalho abordamos o problema de escolha de um algoritmo de segmentação adequado. Uma vez que a avaliação de resultados de segmentação é subjetiva e demorada, propomos um método para avaliar algoritmos de segmentação por meio da avaliação da classificação no final do pipeline. Experimentos com esse método mostraram que algoritmos de segmentação distintos podem ser adequados para a identificação de espécies de classes distintas. Portanto, na segunda parte do trabalho propomos um método de classificação que leva em consideração múltiplas segmentações. Especificamente, múltiplas segmentações são calculadas e classificadores são treinados individualmente para cada segmentação, os quais são então combinados para construir o classificador final. Resultados experimentais mostram que a acurácia obtida com a combinação de classificadores é superior em mais de 2% à acurácia obtida com classificadores usando uma segmentação fixa. Os métodos propostos podem ser úteis para a construção de sistemas de identificação de plâncton que sejam capazes de se ajustar rapidamente às mudanças nas características das imagens. / Plankton are microscopic organisms that constitute the basis of the food chain of aquatic ecosystems. They have an important role in the carbon cycle as they are responsible for the absorption of carbon in the ocean surfaces. Detecting, estimating and monitoring the distribution of plankton species are important activities for understanding the role of plankton and the consequences of changes in their environment. Part of these type of studies is based on the analysis of water volumes by means of imaging techniques. Due to the large quantity of generated images, computational methods for helping the process of image analysis are in demand. In this work we address the problem of species identification. We follow the conventional pipeline consisting of target detection, segmentation (contour delineation), feature extraction, and classification steps. In the first part of this work we address the problem of choosing an appropriate segmentation algorithm. Since evaluating segmentation results is a subjective and time consuming task, we propose a method to evaluate segmentation algorithms by evaluating the classification results at the end of the pipeline. Experiments with this method showed that distinct segmentation algorithms might be appropriate for identifying species of distinct classes. Therefore, in the second part of this work we propose a classification method that takes into consideration multiple segmentations. Specifically, multiple segmentations are computed and classifiers are trained individually for each segmentation, which are then combined to build the final classifier. Experimental results show that the accuracy obtained with the combined classifier is superior in more than 2% to the accuracy obtained with classifiers using a fixed segmentation. The proposed methods can be useful to build plankton identification systems that are able to quickly adjust to changes in the characteristics of the images.

published_or_final_version / Ecology and Biodiversity / Doctoral / Doctor of Philosophy

The purpose of this investigation was to identify the zooplankton and phytoplankton found in Lake Mead, to quantify their presence, to elucidate some temporal and spatial patterns, and to investigate some of the planktonic responses to physical, chemical, and biological parameters. Phytoplankton and zooplankton population samples were collected from eight different sites at il depths at six times over an annual period. These samples were collected with a 6-liter Van Dorn sampler. Phytoplankton samples were preserved in Lugol's solution and the zooplankton were placed in formalin preservative. The 503 zooplankton population samples were scored in a ruled counting chamber using a stereomicroscope. Eighteen species of zooplankton were identified. The 274 phytoplankton samples were placed on Millipore filters and slides were prepared for examination with phase contrast microscopy. A total of at least 79 algae were found to comprise the phytoplankton flora. The zooplankton for the most part were rotifers, cladocerans, and copepods. Keratella, the principal rotifer, was found to be diacmic and Bosmina, Daphnia, the calanoid, cyclopoid, and nauplii copepods were monacmic. Spatial relationships across the reservoir indicate that Bosmina and cyclopoid copepods are water quality indicators. The late summer phytoplankton were mostly Cyanophyta with populations as large as 5 x 10⁶ cells/liter occurring in Boulder Basin. Winter samples contained mostly diatoms and cryptomonads, while the spring phytoplankton was mainly Chlorophyta. The early summer flora showed a mixture of Chrysophyta, Chlorophyta, and Cryptophyta. Biomass determinations were made from average cell volumes and population counts. The blue-green alga Oscillatoria had the greatest biomass during the late summer period. Bacillariophyta reached a volumetric peak in late winter and the Chlorophyta in spring. The Cryptophyta showed a peak in winter while the Chrysophyta, represented mostly by the presence of Dinobryon, showed greatest population sizes in early summer. The Euglenophyta and Pyrrophyta were relatively unimportant groups of the biomass, Weak nocturnal migrations were exhibited by Asplanchna sp., Keratella cochlearis, and Bosmina longirostris. This conclusion was derived from an analysis of variance of the diurnal data. The copepod groups showed no migration patterns. Since this study was performed when the lake was isothermal, it is inferred that migration is a phenomenon not influenced by temperature. A transect study in Boulder Basin during the winter showed that Daphnia, Asplanchna, Chydorus, and Polyarthra, and possibly calanoid copepods, appear to be littoral, and are found mostly in the Las Vegas Wash area. Phytoplankton counts showed evidence for decreases in Bacillariophyta, Chlorophyta, Cyanophyta, and Cryptophyta across the basin from the wash to the dam area. Pyrrophyta Chrysophyta, and Euglenophyta were not important in the phytoplankton flora at this season. Nygaard's and Pearsall's ratios and Palmer's pollution- tolerant algae indices were applied to the phytoplankton data. Results of the Nygaard and Pearsall ratios, the migration study, the transect study, and the population studies indicate that Boulder Basin is eutrophic.