The Wastewater Systems Effluent Regulations (WSER), developed under the Fisheries Act, came into force in 2012 to manage wastewater releases by systems that collect an average daily influent volume of 100 cubic metres or more. The WSER also does not apply to any wastewater system located in the Northwest Territories, Nunavut and north of the 54th parallel in the provinces of Quebec and Newfoundland and Labrador. The WSER set national baseline effluent quality standards that are achievable through secondary wastewater treatment. The map below presents data regarding compliance with the WSER effluent quality standards according to their averaging period. Wastewater systems must report on either a monthly, quarterly or annual basis. The dataset also includes the carbonaceous biochemical oxygen demand (CBOD) and suspended solids (SS) results for each wastewater system. Annual reporting: This map layer shows whether or not the wastewater systems met the WSER effluent quality limit according to an annual averaging period for carbonaceous biochemical oxygen demand CBOD or suspended solids SS. Quarterly reporting: This map layer shows whether or not the wastewater systems met the WSER effluent quality standards according to a quarterly averaging period. Note that a system that meets its CBOD limit or its SS limit for more than 75% of the time is considered to be in compliance with the effluent quality standards of the WSER.Monthly reporting: This map layer shows whether or not the wastewater systems met the WSER effluent quality standards according to a monthly averaging period. Note that a system that meets its CBOD limit or its SS limit for more than 75% of the time is considered to be in compliance with the effluent quality standards of the WSER.The map is available in both ESRI REST (to use with ARC GIS) and WMS (open source) formats. For more information about the individual reporting wastewater systems, datasets are available in either CSV or XLS formats.Data from Quebec and YukonThe data for Quebec municipalities (after 2017) is provided to the department separately through the equivalency agreement that was finalized in October 2018. Beginning in 2015, the data reported for the Yukon is provided to the department separately through an equivalency agreement finalized in 2014.More information on the wastewater sector including the regulations, agreements, contacts and resource documents is available at: https://www.canada.ca/wastewater 

The flows and effluent quality data is for the parameters of: * Biological Oxygen Demand BOD5/CBOD5 * Total Suspended Solids (TSS), also described as Residual Particulate Solids * Total Phosphorus (TP) * total monthly flow Keywords: Sewage, Effluent, Discharge, Watershed, Waterworks, Water management, Muncipality

Description:Seasonal mean oxygen concentration from the British Columbia continental margin model (BCCM) were averaged over the 1981 to 2010 period to create seasonal mean climatology of the Canadian Pacific Exclusive Economic Zone.Methods:Oxygen concentrations at up to forty-six linearly interpolated vertical levels from surface to 2400 m and at the sea bottom are included. Spring months were defined as April to June, summer months were defined as July to September, fall months were defined as October to December, and winter months were defined as January to March. The data available here contain raster layers of seasonal oxygen concentration climatology for the Canadian Pacific Exclusive Economic Zone at 3 km spatial resolution and 47 vertical levels.Uncertainties:Model results have been extensively evaluated against observations (e.g. altimetry, CTD and nutrient profiles, observed geostrophic currents), which showed the model can reproduce with reasonable accuracy the main oceanographic features of the region including salient features of the seasonal cycle and the vertical and cross-shore gradient of water properties. However, the model resolution is too coarse to allow for an adequate representation of inlets, nearshore areas, and the Strait of Georgia.

Description:Seasonal mean oxygen concentration from the British Columbia continental margin model (BCCM) were averaged over the 1993 to 2020 period to create seasonal mean climatology of the Canadian Pacific Exclusive Economic Zone.Methods:Oxygen concentrations at up to forty-six linearly interpolated vertical levels from surface to 2400 m and at the sea bottom are included. Spring months were defined as April to June, summer months were defined as July to September, fall months were defined as October to December, and winter months were defined as January to March. The data available here contain raster layers of seasonal oxygen concentration climatology for the Canadian Pacific Exclusive Economic Zone at 3 km spatial resolution and 47 vertical levels.Uncertainties:Model results have been extensively evaluated against observations (e.g. altimetry, CTD and nutrient profiles, observed geostrophic currents), which showed the model can reproduce with reasonable accuracy the main oceanographic features of the region including salient features of the seasonal cycle and the vertical and cross-shore gradient of water properties. However, the model resolution is too coarse to allow for an adequate representation of inlets, nearshore areas, and the Strait of Georgia.

The Standardized Precipitation Evapotranspiration Index (SPEI) is computed similarly to the SPI. The main difference is that SPI assesses precipitation variance, while SPEI also considers demand from evapotranspiration which is subtracted from any precipitation accumulation prior to assessment.Unlike the SPI, the SPEI captures the main impact of increased temperatures on water demand.

Data Description:Monthly mean simulation results from Canada's three Oceans model (sensitivity experiments--2017). Experiment codes can be matched to specific parameter sets following Table 1 in Christian et al 2026 from Canadian Technical Report of Fisheries and Aquatic Sciences 3721.Abstract from the report:A numerical ocean model with biogeochemistry has been developed for a domain that spans Canada's three oceans: the Atlantic, Pacific and Arctic. The domain extends to 26°N in the Atlantic and 44°N in the Pacific, and spans the full width of each basin as well as the whole of the Arctic Ocean. The resolution is moderate to high (≈0.25°, 75 levels). A series of simulations was conducted to assess the best choices for biogeochemical model parameters across the diverse regions, using a variety of validation data sets including satellite ocean colour (surface chlorophyll and particulate organic carbon, integrated primary production), surface underway pCO2, and depth profiles of oxygen and nitrate concentration from ships and Argo floats. An extensive set of parameter sensitivity experiments was conducted which are documented in detail here, with a focus on zooplankton grazing and phytoplankton and zooplankton mortality (linear and quadratic) parameters, and particle sedimentation rates. Sensitivity to many of the parameter adjustments examined is low, but the experiments conducted span the range from weak seasonal biological drawdown of surface inorganic carbon and nutrients, to excessively large drawdown and thermocline oxygen demand. Further, the general nonlinearity of the model response to parameter adjustments is shown by similar parameter sets having very different effects on different data metrics. In addition, the model solution's general insensitivity to some phytoplankton processes (exudation, chlorophyll photooxidation) that are neglected in the 'base case' model simulation is demonstrated. An optimal set of parameters for this domain is proposed, but it is possible that there are unexplored regions of the parameter space that could improve performance, especially if additional observational constraints are applied.

PURPOSE:To quantify impacts of nutrient and sediment loading to plant and animal communities and the environmental conditions that support them in estuaries of the Southern Gulf of St. LawrenceDESCRIPTION:The MEQ monitoring program is being implemented in 35-40 estuaries in the southern Gulf of St. Lawrence (sGSL) to support the development of a MEQ measure (threshold) to promote efforts to address nutrient enrichment in estuaries. The two main indicators included in the monitoring program are dissolved oxygen and eelgrass coverage which are used to assess the trophic status of estuaries within the region. The two factors most important for impacting the trophic status of estuaries are nitrogen loading and water residence time, i.e., water circulation. If water residence time is long and/or nitrogen loading is high, nutrient impacts are likely. A peer-reviewed manuscript has demonstrated that these two factors are predictive of the dissolved oxygen regime in the upper estuary and that publication successfully used dissolved oxygen to ascribe trophic status to estuaries. In a companion paper it was also determined that nitrogen loading was negatively correlated with eelgrass coverage. These two papers form the basis of the MEQ monitoring program (see attached). NOTES ON QUALITY CONTROL:Dissolved oxygen loggers require calibration prior to deployment and are checked for drift after retrieval (though drift isn't anticipated given optical sensor technology). In the event that dissolved oxygen loggers weren't cleared at a frequency sufficient to prevent data errors from occurring these data are removed prior to analysis. Additionally, data must be scrubbed of erroneous measurements which are relatively rare and very apparent. An error code of -888.88 is the primary error for dissolved oxygen loggers. Salinity probes rarely provide erroneous data and when they do it is typically the result of fouling.PHYSICAL SAMPLE DETAILS:Water is sampled bi-weekly to monthly using a Niskin water sampler at a depth of 0.5 m from the water surface, from May-November. Samples are processed in the laboratory in duplicate for chlorophyll a and seston within ~8 hours of being collected.SAMPLING METHODS:For each study estuary, dissolved oxygen is monitored continuously with optical dissolved oxygen loggers in the upper and mid-estuary. Tidal amplitude and salinity (NB and NS only) were also monitored at the upper estuary location only. Depth profiles for other water quality variables are taken at the bi-weekly or monthly scale as well as samples for seston (NB and NS only) and chlorophyll a (a proxy for phytoplankton). These parameters are monitored on a 3-year cycle except for two sites in PE and one site in NB and NS which are monitored annually: West and Wheatley, PE, Cocagne, NB and Pugwash, NS, respectively.Data is collected for eelgrass coverage by a collaborator between June-September, ideally during the same year we collect water quality data.Collaborators include the province of PEI’s Department of Environment, Water and Climate Change and the Southern Gulf of St. Lawrence Coalition on Sustainability.USE LIMITATION:To ensure scientific integrity and appropriate use of the data, we would encourage you to contact the data custodian.

Description:In the coming decades, warming and deoxygenation of marine waters are anticipated to result in shifts in the distribution and abundance of fishes, with consequences for the diversity and composition of fish communities. Here, we combine fisheries-independent trawl survey data spanning the west coast of the USA and Canada with high-resolution regional ocean models to make projections of how 34 groundfish species will be impacted by changes in temperature and oxygen in British Columbia (BC) and Washington. In this region, species that are projected to decrease in occurrence are roughly balanced by those that are projected to increase, resulting in considerable compositional turnover. Many, but not all, species are projected to shift to deeper depths as conditions warm, but low oxygen will limit how deep they can go. Thus, biodiversity will likely decrease in the shallowest waters (less than 100 m), where warming will be greatest, increase at mid-depths (100–600 m) as shallow species shift deeper, and decrease at depths where oxygen is limited (greater than 600 m). These results highlight the critical importance of accounting for the joint role of temperature, oxygen and depth when projecting the impacts of climate change on marine biodiversity.The rasters available in this dataset project the occurrence of each of the 34 groundfish species in a 3 km^2 grid cell for the historical baseline, as well as for two emissions scenarios, from each of the two regional ocean models (BCCM and NEP36). Each projection layer is provided as the mean projected occurrence as well as the lower and upper 95% confidence interval of projected occurrence.Methods:Estimated species response curves:We estimated how the observed distribution of groundfish species is determined by temperature, dissolved oxygen and seafloor depth using data from fisheries-independent scientific research trawls spanning the entire American and Canadian west coast. We included data from 4 surveys (NOAA West Coast, NOAA Alaska, NOAA Bering or DFO Pacific) from 2000 to 2019. For each species, we modelled occurrences in the coastwide trawl dataset using a generalized linear model (GLM) using the sdmTMB package in R v. 4.0.2. The predictors were temperature, log dissolved oxygen, log depth and survey. We included quadratic terms for temperature and log depth to allow species occurrences to peak at intermediate values. We fitted a breakpoint function for log dissolved oxygen to reflect the fact oxygen is a limiting factor. We assessed the forecasting accuracy of the SDM by comparing how well a model fitted to only data from 2000 to 2010 could forecast species’ occurrences in trawls within our focal region for the period of 2011–2019. We assessed all 77 groundfish species that were present in the overall trawl dataset, however the final analysis included only the 34 species for which the models had adequate forecasting ability.Projecting groundfish biodiversity changes:We based our groundfish biodiversity change projections on two regional models that downscale climate projections: the British Columbia Continental Margin model (BCCM) and the North-Eastern Pacific Canadian Ocean Ecosystem model (NEP36-CanOE). We used a historical baseline of 1986–2005 and future projected values for 2046–2065 based on RCP 4.5 and 8.5 emissions scenarios. Using the models that we validated in our forecasting accuracy assessment, we projected the occurrence of each species in each 3 km^2 grid cell for the historical baseline, as well as for two emissions scenarios, from each of the two regional ocean models.Uncertainties:Source survey data was collected by consistent methods with survey-grade GPS for all years included. Data quality is expected to be high. Modeled data are at 3 km resolution. Outputs are as accurate as source input models and are deemed to be of high quality and accurate based upon the precision of model inputs.Projecting biodiversity responses to climate change involves considerable uncertainty and our approach allows us to quantify some aspects of this. Of the uncertainty that we could quantify, roughly half was due to uncertainty in our SDMs and the remainder was due to regional ocean model uncertainty or scenario uncertainty. This amount of uncertainty in the SDMs is typical, stemming from the fact that contemporary species distributions are also influenced by other factors that we have not included in our model. In addition, although oxygen demand is understood to vary with temperature, limitations in the implementation of breakpoint models prevented us from estimating a temperature-dependent oxygen breakpoint. However, although somewhat unrealistic, this limitation is unlikely to have greatly increased the uncertainty in our SDMs because low oxygen concentrations occurred almost exclusively at depths where temperature variation and projected change was small.To reduce uncertainty due to year-to-year variation in climate, our model projections are based on 20-year climatologies with a future period that is far enough ahead to ensure that changes are unambiguously due to greenhouse gases. We have made projections based on two different emissions scenarios, and two different regional ocean models that are both downscaled from the same global model, the second generation Canadian Earth System Model (CanESM2), using different downscaling techniques. While the BCCM model was run inter-annually and then averaged to produce the climatologies, the NEP36 model used atmospheric climatologies with augmented winds to force the ocean model and produce representative climatologies. Comparing these regional projections provides an estimate of the uncertainty across different regional downscaling models and methods. We find that the projected impacts of climate change on the groundfish community are more sensitive to the differences in the regional ocean models than they are to the emissions scenarios used. However, these differences are in magnitude (changes tend to be larger based on NEP36 compared with the BCCM) rather than in direction, with both models resulting in similar overall patterns of biodiversity change and turnover for the groundfish community. Over the 60-year time period (1986–2005 versus 2046–2065) used in our study, our projections suggest that groundfish community changes are similar regardless of the scenario used.

The excessive input of nitrogen derived from human land-use activities remains a major cause of the eutrophication of coastal ecosystems around the world. However, little data exist on rates of nutrient pollution or its potential impacts to coastal ecosystems in Atlantic Canada. To fill this knowledge gap, a Nitrogen Loading Model (NLM) framework was applied to determine the Total Nitrogen Load (kg TN / yr) from point and non-point source inputs (wastewater, atmospheric deposition, land use, fertilizer applications, and regional industries) in 109 coastal watersheds bordering the Bay of Fundy and Scotian Shelf. To evaluate the potential impact of nitrogen loading, two indicators were calculated for 40 coastal embayments: (1) ∆N, a measure of nitrogen residency that predicts dissolved oxygen problems; and (2) the estuary loading rate, a predictor of the potential for loss of submerged aquatic vegetation. This project was funded by Fisheries and Oceans Canada through a Strategic Program for Ecosystem-based Research and Advice (SPERA) grant. This research has been published in the scientific literature (Kelly et al. 2021). Kelly, N.E., Guijarro-Sabaniel, J. and Zimmerman, R., 2021. Anthropogenic nitrogen loading and risk of eutrophication in the coastal zone of Atlantic Canada. Estuarine, Coastal and Shelf Science, 263, p.107630. doi: https://doi.org/10.1016/j.ecss.2021.107630Cite this data as: Kelly, N.E., Guijarro-Sabaniel, J. and Zimmerman, R. Data of: Estimates of anthropogenic nitrogen loading and eutrophication indicators for the Bay of Fundy and Scotian Shelf. Published: February 2022. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/08746031-1970-4bf6-b6d4-3de2715c8634

The “Biomass Inventory Cartographic Layer” dataset provides the information that is used with the Biomass Report Framework to generate a visual representation of the availability of agricultural and forestry biomass and municipal solid waste in Canada. In addition to yield and production information for biomass produced by the agricultural and forestry industries, this dataset also provides information about the demand for agricultural residues for cattle feed and bedding, tillage systems currently in use on agricultural lands, and land suitability for hybrid poplar and willow plantations that are grown specifically to produce biomass.Agricultural information includes the median annual residue yield and available residue amounts. Residue yields were calculated using crop-to-residue ratios. The available residue information includes the amount that is available after adjusting for the estimated demand of straw used for cattle feed and bedding. Forestry estimates include average residue production, based on forestry activities including permitted amounts of harvesting, mills in operation and mill production.Municipal Solid Waste information includes organic waste (food and yard), paper waste and total residential municipal solid waste (which includes organic and paper waste, among others).