Improving the representation of stream water sources in surrogate nutrient models with water isotope data.

An important part of meeting nutrient reduction goals in the lower Great Lakes basin and assessing the success of different land management strategies is modeling nutrient losses from agricultural land. This study aimed to improve the representation of water source contributions to streamflow in generalized additive models for predicting nutrient fluxes from three headwater agricultural streams in southern Ontario monitored during the Multi-Watershed Nutrient Study (MWNS). The previous development of these models represented baseflow contributions to streamflow using the baseflow proportion derived using an uncalibrated recursive digital filter.

Total and dissolved phosphorus losses from agricultural headwater streams during extreme runoff events.

Eutrophication continues to be a concerning global water quality issue. Managing and mitigating harmful algal blooms demands clear information on the conditions promoting large phosphorus losses from contributing watersheds. Of particular concern is the amount and form of phosphorus loading to receiving water bodies during extreme runoff events, which are expected to increase in frequency due to climate change.

Agricultural intensification leads to higher nitrate levels in Lake Ontario tributaries.

Eutrophication remains the most widespread water quality impairment globally and is commonly associated with excess nitrogen (N) and phosphorus (P) inputs to surface waters from agricultural runoff. In southern Ontario, Canada, increases in nitrate (NO-N) concentrations as well as declines in total phosphorus (TP) concentration have been observed over the past four decades at predominantly agricultural watersheds, where major expansions in row crop production at the expense of pasture and forage have occurred. This study used a space-for-time approach to test whether 'agricultural intensification', herein defined as increases in row crop area (primarily corn-soybean-winter wheat rotation) at the expense of mixed livestock and forage/pasture, could explain increases in NO-N and declines in TP over time.

Novel predictors related to hysteresis and baseflow improve predictions of watershed nutrient loads: An example from Ontario's lower Great Lakes basin.

Eutrophication has re-emerged in the lower Great Lakes basin resulting in critical water quality issues. Models that accurately predict nutrient loading from streams are needed to inform appropriate nutrient management decisions. Generalized additive models (GAMs) that use surrogate data from sensors to predict nutrient loads offer an alternative to commonly applied linear regression and may better handle relationship non-linearities and skewed water quality data.

Suitability of a cytotoxicity assay for detection of potentially harmful compounds produced by freshwater bloom-forming algae.

Detecting harmful bioactive compounds produced by bloom-forming pelagic algae is important to assess potential risks to public health. We investigated the application of a cell-based bioassay: the rainbow trout gill-w1 cytotoxicity assay (RCA) that detects changes in cell metabolism. The RCA was used to evaluate the cytotoxic effects of (1) six natural freshwater lake samples from cyanobacteria-rich lakes in central Ontario, Canada; (2) analytical standards of toxins and noxious compounds likely to be produced by the algal communities in these lakes; and (3) complex mixtures of compounds produced by cyanobacterial and chrysophyte cultures.