The province of PEI has been monitoring dissolved oxygen in some Island estuaries since 2015.

The province of PEI has been monitoring dissolved oxygen in some Island estuaries since 2015.

The Lake Simcoe lake monitoring program provides measurements of chemical and physical water quality limits such as total phosphorus, nitrogen, chlorophyll a, pH, alkalinity, conductivity, dissolved organic and inorganic carbon, silica, other ions, water transparency, temperature and dissolved oxygen. Samples are collected biweekly during the spring, summer and fall. *[pH]: potential of hydrogen

Bottom dissolved oxygen time series at the 3 fixed stations and 46 stations, grouped into transects, of the Atlantic Zonal Monitoring Program (AZMP) under the Quebec region responsibility.The mean bottom dissolved oxygen of the last ten years are displayed as 2 layers, one for the June survey (2014-2023, 2020 not sampled), another for the autumn survey (2014-2023). A third layer shows the positions of the fixed stations of the program (Anticosti Gyre, Gaspé Current and Rimouski).Each station is linked with a .png file showing the bottom dissolved oxygen time series and with a .csv file containing all the bottom dissolved oxygen data acquired at those stations since the beginning of the program sampling (columns : Station, Latitude, Longitude, Date(UTC), Sounding(m), Depth/Profondeur(m), Dissolved_Oxygen/Oxygène_Dissous(%sat)).PurposeThe Atlantic Zone Monitoring Program (AZMP) was implemented in 1998 with the aim of increasing the Department of Fisheries and Oceans Canada’s (DFO) capacity to detect, track and predict changes in the state and productivity of the marine environment.The AZMP collects data from a network of stations composed of high-frequency monitoring sites and cross-shelf sections in each following DFO region: Québec, Gulf, Maritimes and Newfoundland. The sampling design provides basic information on the natural variability in physical, chemical, and biological properties of the Northwest Atlantic continental shelf. Cross-shelf sections sampling provides detailed geographic information but is limited in a seasonal coverage while critically placed high-frequency monitoring sites complement the geography-based sampling by providing more detailed information on temporal changes in ecosystem properties.In Quebec region, two surveys (46 stations grouped into transects) are conducted every year, one in June and the other in autumn in the Estuary and Gulf of St. Lawrence. Historically, 3 fixed stations were sampled more frequently. One of these is the Rimouski station that still takes part of the program and is sampled about weekly throughout the summer and occasionally in the winter period.Annual reports (physical, biological and a Zonal Scientific Advice) are available from the Canadian Science Advisory Secretariat (CSAS), (http://www.dfo-mpo.gc.ca/csas-sccs/index-eng.htm).Devine, L., Scarratt, M., Plourde, S., Galbraith, P.S., Michaud, S., and Lehoux, C. 2017. Chemical and Biological Oceanographic Conditions in the Estuary and Gulf of St. Lawrence during 2015. DFO Can. Sci. Advis. Sec. Res. Doc. 2017/034. v + 48 pp.Supplemental InformationBottom dissolved oxygen is determined from CTD profile in the water column according to AZMP sampling protocol:Mitchell, M. R., Harrison, G., Pauley, K., Gagné, A., Maillet, G., and Strain, P. 2002. Atlantic Zonal Monitoring Program sampling protocol. Can. Tech. Rep. Hydrogr. Ocean Sci. 223: iv + 23 pp.

Deep water (> 200 m) dissolved oxygen interpolated on a grid cell of 10 km x10 km in the Estuary and Gulf of St. Lawrence. Input data are from the annual August multidisciplinary survey hold in 2014 to 2023.PurposeSince 1990, the Department of Fisheries and Oceans has been conducting an annual multidisciplinary survey in the Estuary and northern Gulf of St. Lawrence using a standardized protocol. These surveys are an important source of information about the status of the marine ressources. The objectives of the survey are multiple: to estimate the abundance and biomass of groundfish and invertebrates, to identify the spatial distribution and biological characteristics of these species, to monitor the biodiversity of the Estuary and the northern Gulf and finally, to describe the environmental conditions observed in August in the sampling area.Annual reports are available at the Canadian Science Advisory Secretariat (CSAS), (http://www.dfo-mpo.gc.ca/csas-sccs/index-eng.htm).Bourdages, H., Brassard, C., Desgagnés, M., Galbraith, P., Gauthier, J., Légaré, B., Nozères, C. and Parent, E. 2017. Preliminary results from the groundfish and shrimp multidisciplinary survey in August 2016 in the Estuary and northern Gulf of St. Lawrence. DFO Can. Sci. Advis. Sec. Res. Doc. 2017/002. v + 87 p.Supplemental InformationThe bottom dissolved oxygen is determined from a CTD profile in the water column according to AZMP sampling protocol:Mitchell, M. R., Harrison, G., Pauley, K., Gagné, A., Maillet, G., and Strain, P. 2002. Atlantic Zonal Monitoring Program sampling protocol. Can. Tech. Rep. Hydrogr. Ocean Sci. 223: iv + 23 pp.

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.

In 2010, for the Alberta Geological Survey Saline Aquifer Mapping Project, we collected and analyzed 38 water samples from oil wells producing from geological units, including the Glauconitic, Ostracod, Ellerslie, Banff, Wabamun, Nisku, Leduc and Cooking Lake, within 100 km of Edmonton, Alberta. We analyzed filtered water samples for pH, density and specific conductance. oxygen, hydrogen and strontium isotopes. and dissolved constituents, including sodium, potassium, calcium, magnesium, barium, strontium, lithium, iron, manganese, chloride, bromide, sulphate, sulphide, silica and inorganic carbon.

This project was completed by the Coastal Environmental Baseline Program (Coastal and Freshwater Ecology Section) in the Newfoundland and Labrador Science Branch of Fisheries and Oceans Canada (DFO). From 2020-2023, there were semi-annual deployments and retrievals of 3 moored CTDs in the bay. From 2020 to November 2021, moored CTDs collected hourly recordings of conductivity, temperature and pressure. From 2021 through 2023, these CTDs collected year-round, hourly, information on temperature, conductivity, pressure, dissolved oxygen, and chlorophyll-a. Acoustic releases also collected hourly ambient noise (mV) data. This record contains the geographic locations of the sites, and information on the timings and types of data collected at each site.

Data on physical conditions in Ontario’s lakes and streams: * For lakes this includes measurements such as temperature, dissolved oxygen levels and water transparency, ice dates, as well as sampling location details. * For streams this includes measurements such as stream flow discharge from monitoring stations in south-central Ontario. Meteorological conditions for climate stations close to monitored lakes in south-central Ontario, includes measurements such as air temperature, humidity, precipitation and wind speed. This data set includes information on sampling locations and physical conditions in lakes and streams across Ontario, as well as meteorological and lake ice-cover conditions from monitoring stations in south-central Ontario. Data were collected since 1976, as part of routine monitoring of water quality of inland waters and for scientific and research purposes. Keywords: water quality, meteorology, hydrology, wind, dissolved oxygen, environmental monitoring

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.