The Global Deterministic Wave Prediction System (GDWPS) produces wave forecasts out to 120 hours in the future using the third generation spectral wave forecast model WaveWatch III® (WW3). The model is forced by the 10 meters winds and the ice concentration from the Global Deterministic Prediction System (GDPS). The ice concentration is used by the model to attenuate wave growth in areas covered by 25% to 75% ice and to suppress it for concentration above 75%. Forecast elements include significant wave height, peak period and primary swell height, direction and period.

All stops in the public transport network managed by the City of Rouyn-Noranda**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Coal Agreement feature class contains provincial extent polygon features representing Coal applications, agreements, leases, and licences, with varying term dates and conditions. These applications and subsequent agreements give the holder the right to explore Coal.

Off Road Vehicle (ORV) Trail Plan show the trails (whether individually or by zone) within the off-road vehicle management area or the part of the off-road vehicle management area for which a trail plan is developed, on which an off-road vehicle may be used. A red, yellow, green scheme is used to symbolize the level of restriction on the trail plan. Red: off road vehicles are prohibited; Yellow: off road vehicles are prohibited except where designated by an approved Off Road Management Area Trail Plan; Green: off road vehicles are not prohibitedDistributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@gov.yk. ca](mailto:geomatics.help@yukon.ca)

“4VSW” missions focus on the eastern half of the Scotian Shelf, and occur primarily in March, but sets in both February, and April are also present in the data. These missions use a unique stratification scheme intended to optimize the abundance estimates of cod. Collected data includes total catch in numbers and weights by species. Length frequency data is available for most species, as are the age, sex, maturity and weight information for a subset of the individual animals. Other data such as ageing material, genetic material, and stomach contents are often also collected, but are stored elsewhere.Cite this data as: Clark, D., Emberley, J. Data of Maritimes 4VSW Research Vessel Survey. Published January 2021. Population Ecology Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/a851ce30-e216-4d7d-a29c-05631eef140e

The purpose of this feature class is to identify those areas that are in the process of Timber Harvest Planning, process being a continuum from proposed plan through to approval and eventually plan expiration. Subsection 20(3) of the Forest Resources Act establishes that an approved Timber Harvest Plan is required prior to the authorization of timber harvesting under a Harvesting Licence or authorization of a Forest Resources Permit for non-commercial timber harvesting in an amount greater than 25m3 per year. A Timber Harvest Plan:• Must be developed in accordance with Sections 5 through 7 of the Forest Resources Regulation. • Identifies forest resources in the area and areas suitable for timber harvesting and establishes objectives for timber harvesting.• Must be consistent with any Forest Resources Management Plan that applies to the same area.Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)

An annual trawl survey is conducted in Southwestern Nova Scotia and the Bay of Fundy to assess the lobster stocks in the area. The survey is conducted with the Northeast Fisheries Science Center Ecosystem Survey Trawl (NEST), a small mesh trawl with a cod end liner, which ensures the capture of various sizes of lobster. The dimensions and location of the trawl are monitored and recorded throughout the tow using an electronic trawl mensuration system. In addition, water temperature and depth are also monitored. The target tow length is 1 kilometer which is tracked using an Olex marine charting system. Vessel crew, DFO science staff and a contracted at sea observer work together to perform required tasks and collect all relevant data. Catch from each tow is separated by species, weighed and counted. Length frequency data is collected on select groundfish and crab species and detailed morphometric data is collected on each lobster.PARAMETERS COLLECTED:Set information and profile - includes set date, time depth and locationCatch summary - weight and number caught of each speciesLength Freqeuncies - completed for up to 100 fish for selected speciesLobster Morphological Data - detailed data collected on each lobsterBottom TemperatureTrawl MetricsNOTES ON QUALITY CONTROL:Data is visually verified and double keypunched. On loading to Oracle, data is run through rigorous automated checks to verify data accuracy and integrity.SAMPLING METHODS:The target tow length is 1 kilometer which is tracked using an Olex marine charting system. Vessel crew, DFO science staff and a contracted at sea observer work together to perform required tasks and collect all relevant data. Catch from each tow is separated by species, weighed and counted. Length frequency data is collected on select groundfish and crab species, detailed morphometric data is collected on each lobster. Bottom temperature and trawl metrics are collected for each tow.CITATION LIST:Denton, Cheryl M.. 2020. Maritimes Region Inshore Lobster Trawl Survey Technical Description. Canadian technical reports of fisheries and aquatic sciences (DFO) 3376.

Get a list of provincially licensed operators that collect, transport, process and dispose of deadstock (dead farm animals) in Ontario. This dataset includes facility type, name, location/region and contact information of licensed deadstock operators in Ontario. The Ministry of Agriculture, Food and Agribusiness and the Ministry of the Environment, Conservation and Parks, in consultation with stakeholders, have developed regulations for the disposal of deadstock (dead farm animals) in Ontario. The regulations provide more disposal options for livestock producers and meat plant operators, with measures to protect the environment.

“Summer” missions occur in June, July and August and these focus on the Scotian Shelf and Bay of Fundy (i.e. 4VWX 5Yb, expanding recently to include the Laurentian Channel and Georges Bank (5Zc). Collected data includes total catch in numbers and weights by species. Length frequency data is available for most species, as are the age, sex, maturity and weight information for a subset of the individual animals. Other data such as ageing material, genetic material, and stomach contents are often also collected, but are stored elsewhere.“Summer” cruises occur in May, June, July and August and these focus on the Scotian Shelf and Bay of Fundy (i.e. 4VWX).Cite this data as: Clark, D., Emberley, J. Data of MARITIMES SUMMER RESEARCH VESSEL SURVEYS. Published January 2021. Population Ecology Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/1366e1f1-e2c8-4905-89ae-e10f1be0a164

Description:Data on recreational boating are needed for marine spatial planning initiatives in British Columbia (BC). Vessel traffic data are typically obtained by analyzing automatic identification system (AIS) vessel tracking data, but recreational vessels are often omitted or underrepresented in AIS data because they are not required to carry AIS tracking devices. Transport Canada’s National Aerial Surveillance Program (NASP) conducted aerial surveys to collect information on recreational vessels along several sections of the BC coast between 2018 and 2022. Recreational vessel sightings were modeled against predictor variables (e.g., distance to shore, water depth, distance to, and density of marinas) to predict the number of recreational vessels along coastal waters of BC.The files included here are:--A Geodatabase (‘Recreational_Boating_Data_Model’), which includes: (1) recreational vessel sightings data collected by NASP in BC and used in the recreational vessel traffic model (‘Recreational_Vessels_PointData_BC’); (2) aerial survey effort (or number of aerial surveys) raster dataset (‘surveyeffort’); and (3) a vector grid dataset (2.5 km resolution) containing the predicted number of recreational vessels per cell and predictor variables (‘Recreational_Boating_Model_Results_BC).--Scripts folder which includes R Markdown file with R code to run the modelling analysis (‘Recreational_Boating_Model_R_Script’) and data used to run the code.Methods:Data on recreational vessels were collected by NASP during planned aerial surveys along pre-determined routes along the BC coast from 2018 to 2022. Data on non-AIS recreational vessels were collected using video cameras onboard the aircraft, and data on AIS recreational vessels using an AIS receiver also onboard the aircraft. Recreational boating predictors explored were: water depth, distance to shore, distance to marinas, density of marinas, latitude, and longitude. Recreational vessel traffic models were fitted using Generalized Linear Models (GLM) R packages and libraries used here include: AED (Roman Lustrik, 2021) and MASS (Venables, W. N., Ripley, 2002), pscl package (Zeileis, Kleiber, and Jackman, 2008) for zeroinfl() and hurdle() function. Final model was selected based on the Akaike’s information criterion (AIC) and the Bayes’ information criterion (BIC). An R Markdown file with code use to run this analysis is included in the data package in a folder called Script. Spatial Predictive Model: The selected model, ZINB, consist of two parts: one with a binomial process that predicts the probability of encountering a recreational vessel, and a second part that predicts the number of recreational vessels via a count model. The closer to shore and to marinas, and the higher the density of marinas, the higher the predicted number of recreational vessels. The probability of encountering recreational vessels is driven by water depth and distance to shore. For more information on methodology, consult metadata pdf available with the Open Data record.References:Serra-Sogas, N. et al. 2021. Using aerial surveys to fill gaps in AIS vessel traffic data to inform threat assessments, vessel management and planning. Marine Policy 133: 104765. https://doi.org/10.1016/j.marpol.2021.104765Data Sources:Recreational vessel sightings and survey effort: Data collected by NASP and analyzed by Norma Serra to extract vessel information and survey effort (more information on how this data was analyzed see SerraSogas et al, 2021). Bathymetry data for the whole BC coast and only waters within the Canadian EEZ was provided by DFO – Science (Selina Agbayani). The data layer was presented as a raster file of 100 meters resolution. Coastline dataset used to estimate distance to shore and to clip grid was provided by DFO – Science (Selina Agbayani), created by David Williams and Yuriko Hashimoto (DFO – Oceans). Marinas dataset was provided by DFO – Science (Selina Agbayani), created by Josie Iacarella (DFO – Science). This dataset includes large and medium size marinas and fishing lodges. The data can be downloaded from here: Floating Structures in the Pacific Northwest - Open Government Portal (https://open.canada.ca/data/en/dataset/049770ef-6cb3-44ee-afc8-5d77d6200a12)Uncertainties:Model results are based on recreational vessels sighted by NASP and their related predictor variables and not always might reflect real-world vessel distributions. Any biases caused by the opportunistic nature of the NASP surveys were minimized by using survey effort as an offset variable.