| Eutrophication is a persistent condition of surface waters and a widespread environmental problem. The current state of aquatic ecosystems reflects the anthropogenic impact on processes, chemistry and hydrology; thus understanding relationships between land use and stream biogeochemistry is essential to mitigating eutrophication.;In a two-year study of the Kalamazoo River/Lake Allegan Watershed (KRLAW), a phosphorus (P) total maximum daily load (TMDL) watershed located in southwest Michigan, USA, patterns are identified in suites of chemicals and their relationship to land use to understand the cycling (sources, pathways, fate) of chemicals in the watershed. Although this has been done for P, patterns have not been easily identified with few and weak relationships. Two reasons are proposed for these poor relationships. First, multiple and competing effects on P from temporal (climate, hydrology), catchment (land use, fertilizer application, soil type) and biological (algal productivity, macro-invertebrate grazing) influences. Second, structural restrictions (parameter variance, covariance and correlation) not easily addressed by common statistical methods. Overcoming these deficiencies produces numerous and stronger relationships providing insight into dissolved P (DP) cycling.;The overall hypothesis is DP, stream biogeochemistry and land use have unique relationships and patterns that can be quantified and that DP cycles have characteristic biogeochemical/land use signatures. If true, biogeochemical/land use signatures can be used to identify processes that control DP cycling and outcomes predicted for P mitigation. To test this hypothesis, data is segregated by influence based on biological indicators. Mixed linear models, statistical methods that address parameter covariance and correlation, are used to quantify catchment and biological temporal trends and site effects. Removing these effects, general linear models and principal factor analyses produce improved relationships between DP, stream chemistry and land use.;The catchment influence relationships identify DP source and process correlations with land use. An approach for evaluating DP exports based on readily available land use data is presented. The biological influence analysis identifies impoundment serial discontinuity processes that disconnect the stream system from the landscape, control P cycling and regulate downstream P forms.;Temporal, catchment and biological inferred DP cycling are used to develop an empirical total P (TP) model, based on historical data, to predict Lake Allegan inlet concentrations. The TP model predicts a 63% probability of attaining the 2012 TMDL goal of 72 mug L-1 and mean discharge adjusted 2012 concentration of 65.7mug L-1.;Results from this study provide insight into the P cycling in a mixed land use watershed and have implications for watershed assessment, P reduction strategies and regulatory TMDL policies. |
