Preliminary Impacts of Constructed Log Jams on Streambed Topography and Bed Temperature on the South Fork Nooksack River
Salmon are an essential part of the culture, ecology and economy of the Pacific Northwest region of North America, but populations of some ecotypes are declining. One specific population, the Puget Sound chinook (Oncorhynchus tshawytscha), is listed as threatened under terms of the U.S. Endangered S...
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| Format: | Text |
| Language: | English |
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Western CEDAR
2019
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| Online Access: | https://cedar.wwu.edu/wwu_honors/129 https://cedar.wwu.edu/cgi/viewcontent.cgi?article=1128&context=wwu_honors |
| Summary: | Salmon are an essential part of the culture, ecology and economy of the Pacific Northwest region of North America, but populations of some ecotypes are declining. One specific population, the Puget Sound chinook (Oncorhynchus tshawytscha), is listed as threatened under terms of the U.S. Endangered Species Act (ESA). The decline of this ecotype has implications not only for humans but also for all links of the ecosystem such as the populations of southern resident killer whales (Orcinus orca) which prey predominately on chinook salmon. Major threats to these fish include overharvest and habitat degradation due to anthropogenic factors. In an effort to help the recovery of these fish, and all salmon species, many habitat restoration projects have focused on the construction of engineered log jam (ELJ) structures. This investigation seeks to evaluate the effectiveness of such structures to create deep pools and provide pockets of thermal and velocity refuge for salmon in thermally impaired waters. Spline interpolation and overlay of temperature data was conducted using ArcGIS Pro for bed topography and temperature data collected at plots on the South Fork of the Nooksack River. A before-after control-impact study design was used. Preliminary results show equivocal differences in bed topography before and after ELJ construction (2/4 plots got significantly deeper). Temperature showed no significant effect with respect to treatment. Finally, a Python script was written to efficiently recreate this analysis in future years once more data have been collected. |
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