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A geographical framework for assessing longitudinal patterns in stream habitat and fish distribution

ScholarsArchive at Oregon State University

Field Value
Title A geographical framework for assessing longitudinal patterns in stream habitat and fish distribution
Names Torgersen, Christian E. (creator)
Date Issued 2002-02-25 (iso8601)
Note Graduation date: 2002
Abstract New approaches are needed to quantify and understand spatial patterns of stream fishes and their environment. Concepts in riverine ecology emphasize the importance of thermal zones and gradual longitudinal changes in physical habitat and biota, but little is known about spatial variability within the river continuum. I present a conceptual framework for assessing patterns in streams that are difficult to detect using standard site-based approaches to sampling. The ability to detect pattern is defined as the scope, or the ratio of extent (the distance, area, or volume encompassing all sample points) to grain size (the size of an individual sample unit). By increasing the scope and continuity of sampling, I illustrate how greater sampling effort can
reveal new patterns and unexpected relationships between stream fishes and their
environment. Merging geography and stream ecology, I describe new approaches including remote sensing, multiscale sampling, and extensive surveys for assessing longitudinal patterns in stream habitat and fish distribution. Airborne thermal infrared
remote sensing was effective for quantifying spatially continuous patterns of water
temperature over a range of scales from channel units (10–50 m) to entire river
sections (30–70 km). To examine factors influencing the spatial distribution of larval Pacific lamprey, a benthic fish species, I applied a nested sampling design and determined that stream habitat variables predicted patterns in larval abundance but
played different roles at different spatial scales. Increases in the scope of data
collection required adaptations in statistical analysis in order to accommodate larger and more complex ecological datasets. I evaluated multivariate ordination techniques with respect to their ability to describe fish community structure and found that nonparametric multivariate smoothing of presence–absence data was highly effective for detecting patterns in heterogeneous fish assemblage data. Spatially continuous
analysis presented challenges in extracting patterns from noisy ecological data but
provided the opportunity to evaluate distributional patterns over a range of spatial scales. I examined spatial variability of stream fish assemblages and observed that the relative influences of temperature and channel morphology on fish assemblage structure were dependent on the thermal context and the spatial scale of analysis.
Genre Thesis
Topic Freshwater fishes -- Ecology
Identifier http://hdl.handle.net/1957/9825

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