Thesis (M.S.)--Michigan State University. Dept. of Fisheries and Wildlife, 2006. / Title from PDF t.p. (viewed on June 19, 2009) Includes bibliographical references (p. 39-40). Also issued in print.

Thesis (M.S.)--Oregon State University, 2006. / Printout. Includes bibliographical references (leaves 82-87). Also available on the World Wide Web.

Thesis (Ph.D.)--Kent State University, 2005. / Title from PDF t.p. (viewed Aug. 23, 2006). Advisor: Laura G. Leff. Keywords: bacterial communities; substrate; lotic; fluorescent in situ hybridization; sediment. Includes bibliographical references.

Thesis (M.S.)--Oregon State University, 2008. / Printout. Includes bibliographical references (leaves 57-68). Also available on the World Wide Web.

Doctor of Philosophy / Division of Biology / Keith B. Gido / This dissertation consists of three research-based chapters which focus on habitat association of prairie stream fishes and how these fish communities influence stream ecosystem properties. Chapter one introduces important concepts used throughout the chapters, and describes my study streams. In chapter two, I identify local habitat factors associated with the diversity and density of fishes in two protected prairie watersheds. Specifically, the relative importance of habitat factors associated with fish communities were evaluated along a stream-size gradient and across multiple seasons and years. I found that species richness was positively associated with pool area and discharge. Redundancy analyses showed common prairie fish species exhibit ontogenetic habitat associations, with adults in deep and juveniles in shallow pools. Chapter 3 addresses how fish species richness in small prairie streams affects whole-stream metabolism and biomass distribution of benthic organic matter, algal and macroinvertebrates. This study was conducted by stocking experimental stream mesocosms that included pool-riffle habitats with three different communities that represent a gradient of species richness of headwater prairie streams from one to three common prairie stream fish species. I illustrated how species influence ecosystems across multiple spatial scales and found that different communities altered the distribution of algal biomass from benthic surfaces to floating mats and from pools to riffles. The objective of the fourth chapter was to quantify how two size classes of herbivorous prairie stream fish species, central stoneroller Campostoma anamolum and southern redbelly dace Chrosomus erythrogaster differentially affect stream ecosystem properties. This study was also conducted in experimental stream mesocosms, where each unit consisted of one riffle and one pool. Using ANOVAs, I found large dace were associated with longer filaments (F = 7.5, P = 0.002, df = 4) and small fishes with less benthic organic matter (F = 4.2, P = 0.02, df = 4). There was no evidence for ontogenetic shifts in diet and likely differences in energetic requirements and behavior drove the differences among treatments. My research finds that small-bodied prairie stream fishes have predictable habitat preferences and effects on stream properties are dependent on species identity, richness and size structure.

published_or_final_version / Botany / Master / Master of Philosophy

published_or_final_version / Ecology and Biodiversity / Master / Master of Philosophy

The aim of the project was to determine factors which explain the distribution of macroinvertebrates in two Melbourne streams both drastically affected by urbanisation. A detailed description is given of Dandenong Creek, flowing through the south-eastern suburbs, and Darebin Creek, in the northern suburbs, emphasising stream features likely, or known, to influence the drift and benthic fauna. Faunal sampling was carried out in Dandenong Creek from June 1992 until July 1993, and in Darebin Creek from February 1995 until March 1998. Physicochemical parameters were also recorded. The collected data, together with previously existing data, were analysed using multivariate analyses: non-metric multi-dimensional scaling (NMDS); analysis of similarities (ANOSIM); matching biotic and abiotic variables using BIOENV, and principal component analysis (PCA). Various biotic and diversity indices were calculated in an attempt to identify the major factors responsible for the failure of the fauna to recover from previously more seriously degraded water quality. The contribution of drift to the colonisation potential in Dandenong Creek appeared to be impacted by retarding basins, underground barrel-draining and channelization. Results also indicated that increased conductivity adversely affected the fauna in the lower reaches of Dandenong Creek. It was concluded that in Darebin Creek, high nutrient levels, as well as other pollutants, had resulted in low macroinvertebrate diversity in both the drift and benthos. If, as this study suggests, faunal diversity is a valid measure of stream health, the following factors need to be addressed for catchment-wide, stream management: lack of riparian zone vegetation (increasing bank erosion and making the benthic habitat unstable, with greater temperature variability); control of stormwater runoff (flow variability, increased conductivity, nutrient levels, sediment loads, sewage effluent, industrial discharges and heavy metals), and to modify retarding basins to increase stream continuity.

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.)--Oregon State University, 2008. / Printout. Includes bibliographical references (leaves 126-140). Also available on the World Wide Web.