Identifying Seasonal Trends In Dissolved Phosphorus In a Mixed Land Use Watershed Using a Mixed Linear Model Approach
In the Kalamazoo River study, weekly stream chemistry measurements and land use data were segregated into landscape and algal influenced datasets. Each was analyzed using a MLM incorporating variables for year and week within year. The landscape MLM identified a DP seasonal trend related to a similar trend in baseflow. The MLM yielded statistical significance (p<0.05) for nitrate, potassium, magnesium, sodium, pH, alkalinity, specific conductance and urban, agricultural and lowland forest land uses. The algal MLM identified a year effect related to differences in algal productivity and statistical significance (p<0.05) for particulate P, nitrate, sulphate, calcium, pH and specific conductance. These results indicate that the MLM provides a method to model not only the means of data but their variances and covariances as well.
Fitting a MLM that includes the seasonal effects allows inferences to be drawn about the DP cycling from the significant fixed effects and the covariance parameters.