The province of PEI has been monitoring dissolved oxygen in some Island estuaries since 2015. This dataset contains data collected in 2022. Monitoring results from earlier years can also be found on the Prince Edward Island open data portal.This dataset includes raw data from 20 Island estuaries from across PEI; mapped locations of monitoring sites; and downloadable raw data. The data includes dissolved oxygen concentration, dissolved oxygen saturation, water temperature and instrument depth. Data is usually collected between May and October of each year. 18 estuaries are monitored on a 3 year rotating cycle with at least 6 of these 18 monitored in any given year. Another 2 estuaries are monitored every year. 2 locations are monitored in each estuary; the Upper Estuary location represents the upper 10% boundary of the estuary’s surface area, is closest to the freshwater inputs and should display signs of eutrophication if they are present; the Mid Estuary location represents the mid-point or 50% boundary of the surface area of the estuary. The Mid Estuary site may have two loggers, one placed about 0.5 m the bottom substrate and one placed about 0.5 m from the surface of the water. Data may be used to determine hourly fluctuations in oxygen, the degree of eutrophication, and the presence and duration of anoxia and hypoxia. Temperature and instrument depth (not the same as water depth at the site) data are also collected and available for use.

This is a point layer of the names and locations of the actively used commercial shipping anchorages in British Columbia. These point locations were manually compiled from available port guides and documents. The objective of this dataset is to provide a consolidated file containing all active commercial shipping anchorage locations as there has been a lack of consistency between different sources due to variations in names and locations in different datasets and historical changes to anchorage locations.

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 province of PEI has been monitoring dissolved oxygen in some Island estuaries since 2015. This dataset contains data collected from 2015 to 2021. Monitoring results from later years can also be found on the Prince Edward Island open data portal.This dataset includes raw data from 20 Island estuaries from across PEI; mapped locations of monitoring sites; and downloadable raw data. The data includes dissolved oxygen concentration, dissolved oxygen saturation, water temperature and instrument depth. Data is usually collected between May and October of each year. 18 estuaries are monitored on a 3 year rotating cycle with at least 6 of these 18 monitored in any given year. Another 2 estuaries are monitored every year. 2 locations are monitored in each estuary; the Upper Estuary location represents the upper 10% boundary of the estuary’s surface area, is closest to the freshwater inputs and should display signs of eutrophication if they are present; the Mid Estuary location represents the mid-point or 50% boundary of the surface area of the estuary. The Mid Estuary site may have two loggers, one placed about 0.5 m the bottom substrate and one placed about 0.5 m from the surface of the water. Data may be used to determine hourly fluctuations in oxygen, the degree of eutrophication, and the presence and duration of anoxia and hypoxia. Temperature and instrument depth (not the same as water depth at the site) data are also collected and available for use.

Thermal Conductivity Observations provided by the Canadian Geothermal Data Compilation for Canada

Thermal Conductivity Observations provided by the Canadian Geothermal Data Compilation for Canada