Graduate Thesis Or Dissertation
 

On the estimation and application of spatial and temporal autocorrelation in headwater streams

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/6h440w092

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  • This collection of three manuscripts serves to improve methods for collecting, interpreting, and utilizing autocorrelated data from headwater stream networks. Each stream network is comprised of linear segments. These segments lie within a unique branching structure that connects the segments via flowing water, and the connectivity provided by water varies seasonally. These aspects separate stream networks from other landscapes, and provide unique challenges to the statistical analysis of stream-based phenomenon. Two chapters of this work relied on a unique and comprehensive set of data. These data constitute a complete census of habitat unit fish counts from 40 randomly selected headwater basins in western Oregon. The first objective of this work was to evaluate how different sampling designs captured spatial autocorrelation, given the samples were drawn from a population of spatially autocorrelated observations. Spatially distributed clusters of sampling locations were more apt to capture spatial autocorrelation than samples without clusters or small clusters located at tributary junctions. A similar investigation was made concerning sampling design performance in relation to estimating autocorrelation function values. All sampling designs lead generally to negatively biased estimates, and practical differences among the sampling designs were not observed. The second objective was to investigate spatial autocorrelation model range parameters as measures of patch sizes. It is common practice to use range parameters to infer the size of patches within spatially autocorrelated data, but this methodology lacks sufficient justification. The census data were used to compute range parameter values, and another proposed autocorrelative measure of patch size: the integral scale. The same data were used to compute patch sizes under several patch definitions, and the relationship of range parameters and integral scale values with patch sizes was explored. Range parameter values did not equal and were not strongly correlated with average patch sizes, though range parameter values were more correlated with maximum patch and gap sizes. Integral scale values matched the magnitude of, but were not strongly correlated with, average patch sizes. The third objective was to refine the analysis of temporally autocorrelated hydrology data from paired watershed studies. Paired watershed studies are used to evaluate forest harvesting effects on stream biota and hydrology (i.e. fish, amphibians, insects, stream flow, and sediment yield). Traditionally, treatment effects are discerned using prediction intervals. This work provided an improved method for constructing prediction intervals for use in change detection in paired watershed studies. The improved prediction intervals included variation associated with estimating linear and autocorrelation model parameters.
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