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Water quality monitoring data collected in priority tributaries to provide nutrient concentration data to estimate nutrient loads to the waters of the Great Lakes. Data is collected to advance the science to understand and address the complex problem of recurrent toxic and nuisance algae in the Great Lakes. The majority of the data is focused on Lake Erie, the smallest, shallowest of the Great Lakes, and most susceptible to nearshore water quality issues. Water quality monitoring is conducted to establish current nutrient loadings from selected Canadian tributaries; to enhance the knowledge of the factors that affect tributary and nearshore water quality, ecosystem health, and algae growth; to establish binational lake ecosystem objectives, phosphorus objectives, and phosphorous load reduction targets, and to support the development of a binational nearshore assessment and management framework.

Water quality and ecosystem health data are collected in the nearshore zone of the Great Lakes to address the problem of nuisance benthic algae. Monitoring data include physical and chemical water quality data as well as biological data, primarily from Cladophora and dreissenid mussels on the lakebed. Monitoring is conducted (i) to improve understanding of the factors impacting nearshore water quality, algae growth, and ecosystem health; (ii) to develop ecosystem health indicators for the nearshore; (iii) to provide validation and calibration data for modelling; (iv) to support the development of a binational nearshore assessment and management framework; and, (v) to measure the success of ongoing and future phosphorus reduction targets to support a healthy ecosystem.

The Great Lakes Basin Integrated Nutrient Dataset compiles and standardizes phosphorus, nitrogen, and suspended solids data collected between the 2000-2019 water years from multiple Canadian and American sources around the Great Lakes. Ultimately, the goal is to enable regional nutrient data analysis within the Great Lakes Basin. This data is not directly used in the Water Quality Monitoring and Surveillance Division tributary load calculations. Data processing steps include standardizing data column and nutrient names, date-time conversion to Universal Time Coordinates, normalizing concentration units to milligram per liter, and reporting all phosphorus and nitrogen compounds 'as phosphorus' or 'as nitrogen'.

Blooms of filamentous benthic algae that plagued Lake Erie in the 1950s through 1970s were largely reduced through reductions of phosphorus (P) loading from point sources. Since the mid-1990s, these blooms have returned despite a period of relatively stable external P inputs. While increased loadings of dissolved P have been causally linked to cyanobacterial blooms in some parts of the lake, the impacts of ecosystem changes such as the effect of invasive species on nutrient cycling and availability have not been fully elucidated, leading to uncertainty as to the effectiveness of additional non-point P management actions. Here we use the oxygen isotope ratios (δ18OP) of phosphate in concert with measures of water quality along the northern shore of the east basin of Lake Erie to identify sources and pathways of P cycling and infer potential importance in relation to annual blooms of Cladophora that foul the shorelines of eastern Lake Erie.

Water quality and ecosystem health data used to conduct a cumulative effects assessment of Lake Superior nearshore waters in support of the Great Lakes Water Quality Agreement are included in this dataset. Data related to nearshore stressors is integrated into an overall assessment in a three-phased approach: 1) classification of the nearshore into Regional Units using physical processes and lake characteristics; 2) overall assessment of the state (cumulative stress) of each Regional Unit; and 3) integrate additional information related to nearshore areas of high ecological value. Assessment data is presented within a 100 metre depth zone along the coast. For purposes of determining stress on nearshore waters it is necessary to consider the zones of influence and zones of impact.

Water quality and ecosystem health data used to conduct a cumulative effects assessment of Lake Ontario, Niagara River and St. Lawrence River nearshore waters in support of the Great Lakes Water Quality Agreement are included in this dataset. Data related to nearshore stressors is integrated into an overall assessment in a three-phased approach: 1) classification of the nearshore into Regional Units using physical processes and lake characteristics; 2) overall assessment of the state (cumulative stress) of each Regional Unit; and 3) integrate additional information related to nearshore areas of high ecological value. Assessment data is presented within a 30 metre depth zone along the coast. For purposes of determining stress on nearshore waters it is necessary to consider the zones of influence and zones of impact.

Water quality and ecosystem health data used to conduct a cumulative effects assessment of Lake Erie, St. Clair River, Lake St. Clair and Detroit River nearshore waters in support of the Great Lakes Water Quality Agreement are included in this dataset. Data related to nearshore stressors is integrated into an overall assessment in a three-phased approach: 1) classification of the nearshore into Regional Units using physical processes and lake characteristics; 2) overall assessment of the state (cumulative stress) of each Regional Unit; and 3) integrate additional information related to nearshore areas of high ecological value. Assessment data is presented within a 15 metre depth zone along the coast. For purposes of determining stress on nearshore waters it is necessary to consider the zones of influence and zones of impact.

Water quality and ecosystem health data collected in the Great Lakes and priority tributaries to determine baseline water quality status, long term trends and spatial distributions, the effectiveness of management actions, determine compliance with water quality objectives and identify emerging issues are included in this dataset.

GBI monitors water quality in coastal wetlands to report on nutrient loads resulting from human use of day-use areas. The park uses Water Quality Index to assess this measure - which is also a part of the Great Lakes Shoreline monitoring network.

Water quality and ecosystem health data used to conduct a cumulative effects assessment of Canadian Great Lakes nearshore waters in support of the Great Lakes Water Quality Agreement are included in this dataset. The data was collected by various government and non-government agencies and organizations and integrated into this dataset to allow the assessment to be conducted. By conducting a regular, systematic assessment of cumulative effects in the nearshore waters of the Great Lakes Environment and Climate Change Canada (ECCC) is able to identify areas of high quality and areas under stress. Knowledge of ecological thresholds, other Great Lakes assessments, stressor information, indicators and local and traditional ecological knowledge will be used to aid in: 1) the identification and mapping of high quality nearshore areas and areas that are or may become subject to high stress and; 2) the determination of factors and cumulative effects that are causing stress or threats.