Identifying Linear Relationships Between Streamflow Metrics And Benthic Macroinvertebrate Metrics In Minnesota
2018-08
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Identifying Linear Relationships Between Streamflow Metrics And Benthic Macroinvertebrate Metrics In Minnesota
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2018-08
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Understanding how the flow of a stream affects the aquatic organisms that depend on it will help users and managers of freshwater protect those organisms. Developing flow-biology relationships is a complicated task, wrought with problems of scale and natural variability. The purpose of this project was to determine if linear relationships could be identified between flow metrics and benthic macroinvertebrate metrics within a watershed at two different analytical scales, using both modeled and observed flow data. By using stepwise linear regression, a variable selection method, to select the most predictive independent variables from a large pool of flow metrics, inferences can be drawn about which components of streamflow have the greatest effect on the benthic macroinvertebrate communities in those streams. Two analytical scales were studied, referred to as “large” and “headwater” watershed scales. The large scale analysis used a more generalized biological variable, the index of biotic integrity, while the headwater scale analysis used more specific community measures, such as richness of clinger taxa. Additionally, the large watershed scale used observed flow measurements, while the headwater analysis used modeled streamflow. Significant (p<0.10) linear regression equations were developed using flow metrics to predict biological variables at both the large and headwater scales, with the models’ adjusted coefficients of determination (〖R ̂ 〗^2) ranging from zero to 0.93. The results of this project represent one small step toward the goal of defining flow-biology relationships in Minnesota that will help meet the Clean Water Act demands to “restore and maintain the chemical, physical, and biological integrity of the Nation’s waters.”
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University of Minnesota M.S. thesis. August 2018. Major: Water Resources Science. Advisor: Joe Magner. 1 computer file (PDF); 68 pages.
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Fitzpatrick, Kara. (2018). Identifying Linear Relationships Between Streamflow Metrics And Benthic Macroinvertebrate Metrics In Minnesota. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/201007.
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