Thesis--Wisconsin. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--University of Texas at Austin, 2005. / Vita. Includes bibliographical references.

Thesis (PH.D.) -- Syracuse University, 2006 / "Publication number AAT 3251826."

Thesis (Ph.D.)--Baylor University, 2008. / Includes bibliographical references (p. 80-86)

Research was completed to determine factors affecting smolt production and overwinter mortality of Atlantic salmon (Salmo salar) stocked as fry in Vermont tributaries of the Connecticut River. Specific focuses included: (1) timing of smolt migration relative to environmental and physiological factors; (2) effect of ice formation on habitats selected and winter distribution of parr; (3) effect of maturation on parr growth and smolt recruitment; and (4) smolt production dynamics and recruitment modeling. Smolt migration timing and recruitment was determined using net weirs and counting fences and mark-recapture and winter habitat studies were completed by night snorkeling. Tributaries differed in the timing of smolt migration with the tributary warming earliest in the spring generally experiencing earlier smolt migration. Initiation and cessation of smolt migratory activity appeared to be linked to smolt physiological development. Peaks in river discharge increased smolt migratory activity after water temperature thresholds were surpassed, yet only while smolts maintained elevated gill Na$\sp+,$ K$\sp+$-ATPase activity. Ice formation caused significant changes in the physical stream environment, including a reduction in the abundance of habitats often selected by parr. Changes in the distribution of parr over the winter generally corresponded to changes in the distribution of high velocity habitats they rarely selected and low velocity habitats they often selected. Mature parr were abundant across and within tributaries. Percent mature in October/November was positively correlated with mean size the preceding June. Studies on individually marked parr showed that mature parr exhibited poorer June to October growth than immature parr resulting in large differences in fall size. Mature parr were recruited to smolt at a reduced frequency relative to immature parr and modeling analysis indicated that this difference resulted primarily from a one-third probability of smolting for mature parr rather than differences in fall to spring survival. Simulation modeling revealed that losses in potential smolt production attributable to parr maturation may be as high as 35% when maturation percentages reach the maximum of 45% observed in this study. It is concluded that smolt physiology, winter habitat, and parr maturation are primary factors affecting smolt production and overwinter mortality of Atlantic salmon stocked as fry.

Modelling of stream macroinvertebrate communities has been widely accepted as an interesting and powerful tool to support water quality assessment and management. Stream Decision Support Framework (SDSF) offers an alternative approach to the current statistical models as Australian River Assessment Scheme (AusRivAs) for the derivation of scientific basis to support management applications regarding fresh water systems. Implementation of Artificial Neural Networks (ANNs) offers a possibility to overcome constraints of the statistical methods in dealing with high nonlinearity of stream data. This thesis includes several case studies illustrating application of Self Organising Map (SOM) and Multilayer Perceptron (MLP) neural networks to various tasks involving analysis, assessment and prediction of stream macroinvertebrates in three Australian states. The data for this study have been provided by the Queensland Department of Natural Resources (NR&M), EPA Victoria and the Department of Land and Water Conservation, New South Wales (NSW). SDSF approach utilises predictive models for both 'referential' and 'dirty-water' approaches. Applicability and high accuracy of ANN models for the purpose of prediction both occurrence of individual taxa and taxonomic richness of stream macroinvertebrates have been demonstrated using data from Victoria and NSW. A comprehensive analysis of salinity sensitivity of stream macroinvertebrate has been demonstrated using both types of ANNs plus statistical methods, and pressure specific Salinity Index was suggested as a measurement of changes within macroinvertebrate communities in response to the secondary salinisation. Scenario analysis of the combined effect of increasing salinity and nutrient load demonstrated predictability and ecological meaningfulness of the Salinity Index. Application of SOM has been demonstrated using the data from Queensland and Victoria in order to analyse natural variability of macroinvertebrate communities between reference sites. SOM component planes provided a valuable insight into the relationships between abiotic variables (as water quality and geoclimatic factors) and distribution of taxa and trophic structure of macroinvertebrate communities. Potential of SOM as data exploration tool has been also demonstrated for the analysis of the output of scenario simulation in order to understand the difference in response to salinisation in different sites. Flexibility and potential of SDSF have been illustrated by using the combination of SOM and MLP, and combination of ANNs with statistical methods. Application of both SOM and Canonical Correspondence Analysis allowed the extraction of additional information and provided convenient visualisation of the relationships between water quality factors and the structure of macroinvertebrate communities. In general, SDSF provides convenient, flexible and accurate approach for the analysis, assessment and prediction of stream biota. In addition to the freedom from the limitations inherent to the traditional statistical methods it allows many more options than currently used modelling frameworks, namely: highly accurate predictions using both 'referential' and 'dirty-water' approaches, sensitivity analysis, scenario analysis and pattern exploration using SOM. / Thesis (Ph.D.)--School of Earth & Environmental Sciences, 2005.

Thesis (Ph. D.)--University of Hong Kong, 2008. / Includes bibliographical references (leaves 88-105) Also available in print.

Thesis (Ph. D.)--University of Hong Kong, 2008. / Includes bibliographical references (leaves 88-105) Also available online.

Thesis (M. Sc. (Zoology and Entomology))--Rhodes University, 2006.