4. Discussion
4.3 Further Analysis
For further analysis and to perform a regression analysis I would calculate a percentage of each land use category for the entire watershed and a percentage land use in an immediate 50 to 300 meter buffer zone. With this data I would like to run an ordinary least squares and Moran’s I analysis to identify any correlation between land use and water quality. This would allow the examination of the relative impacts of watershed scale versus reach or site scale riparian vegetation integrity on water quality. Other studies have shown that widespread removal of vegetation at the watershed scale does impact water quality (Baker, 2003; Hall & Schreier, 1996; Hicks et al., 1991).
The identification of impacts of urban areas on water quality would require more monitoring sites associated with this land use. It would be interesting to identify a relationship between percentage impervious area and water quality parameters. More specific agriculture land use classification would better identify the land use practices that are having the greatest impact on water quality degradation. For example, in this study agriculture land use classification combined hobby farms, berry crops, dairy farms, plowed fields, and fallow fields, because more specific classifications were not available at the time of analysis. Impacts on water quality, however, would be expected to differ among those agriculture land uses.
To visualize how fish are distributed in these watersheds and their abundance I will plot their numbers and species at each water quality monitoring site that I have fish data for. This will allow for more insight into their spatial and temporal distribution and to examine how water quality dictates habitat usage.
For further analysis and to perform a regression analysis I would calculate a percentage of each land use category for the entire watershed and a percentage land use in an immediate 50 to 300 meter buffer zone. With this data I would like to run an ordinary least squares and Moran’s I analysis to identify any correlation between land use and water quality. This would allow the examination of the relative impacts of watershed scale versus reach or site scale riparian vegetation integrity on water quality. Other studies have shown that widespread removal of vegetation at the watershed scale does impact water quality (Baker, 2003; Hall & Schreier, 1996; Hicks et al., 1991).
The identification of impacts of urban areas on water quality would require more monitoring sites associated with this land use. It would be interesting to identify a relationship between percentage impervious area and water quality parameters. More specific agriculture land use classification would better identify the land use practices that are having the greatest impact on water quality degradation. For example, in this study agriculture land use classification combined hobby farms, berry crops, dairy farms, plowed fields, and fallow fields, because more specific classifications were not available at the time of analysis. Impacts on water quality, however, would be expected to differ among those agriculture land uses.
To visualize how fish are distributed in these watersheds and their abundance I will plot their numbers and species at each water quality monitoring site that I have fish data for. This will allow for more insight into their spatial and temporal distribution and to examine how water quality dictates habitat usage.