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We have found 22 datasets for the keyword " archer fiord". You can continue exploring the search results in the list below.
Datasets: 106,156
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22 Datasets, Page 1 of 3
Archer Fiord Phytoplankton Data 2023
PURPOSE:This Archer fiord data is associated with a larger program ArcticCORE, which was created to fulfill knowledge gaps and develop long term protection in the extremely remote Tuvaijuittuq region. The main objectives of this expedition were to improve our comprehension of the key drivers for productive capacity, diversity and ecosystem structure in areas connected to Baffin Bay and Tuvaijuittuq, including Archer fiord.DESCRIPTION:ArcticCORE is a 5-year broader program aiming to characterize Tuvaijuittuq’s unique ecosystem and its influence and connectivity with the adjacent ecosystems to inform sustainable management and conservation initiatives in Tuvaijuittuq and the eastern Arctic. In an Arctic Ocean with rapidly declining sea ice, Tuvaijuittuq area retains the oldest and thickest sea ice, and can act as a refuge for ice-dependent species. This program aims to characterize the Arctic marine ecosystem and establish baseline measurements for future comparisons in the region. From 2023, water collection was carried out at four stations throughout Archer Fiord and analyzed for primary productivity, chlorophyll a, phytoplankton flow cytometry and phytoplankton taxonomy down to the lowest identifiable level. These data will contribute to a better understanding of the key drivers for productive capacity, diversity and ecosystem structure in Archer fiord. Characterization of these upstream areas are relevant for an ecosystem-based approach to fisheries management in Baffin Bay, a priority for DFO and an intrinsic part of mandated activities, as they influence the ecosystem and fisheries resources downstream.
Irrigation equipment suppliers in Ontario
Find information about irrigation equipment suppliers in Ontario who offer specialized equipment or services. These lists are maintained by the Ministry of Agriculture, Food and Agribusiness (OMAFA) and include: * business names * telephone numbers * website addresses (where available) * description of equipment and services These lists do not imply any endorsement or recommendation by the ministry. If you would like to nominate a supplier for inclusion on this page, contact the Agricultural Information Contact Centre at 1-877-424-1300 or [ag.info.omafa@ontario.ca](ag.info.omafa@ontario.ca) for additional support.
Focus Area for the Regional Assessment of Offshore Wind Development in Newfoundland and Labrador
Depicts priority area for work under the Regional Assessment of Offshore Wind Development in Newfoundland and Labrador. The Committee for the Regional Assessment of Offshore Wind Development in Newfoundland and Labrador (Committee) is responsible for providing information, knowledge and analysis regarding future offshore wind development (OSW) to inform and improve future planning, licencing and impact assessment processes. The Committee’s mandate is set out in the Agreement to Conduct the Regional Assessment of Offshore Wind Development in Newfoundland and Labrador (Agreement), and includes assessing potential environmental, health, social and economic effects of future OSW. The Agreement includes a broad Study Area. In November 2023, the Committee determined OSW interest in the foreseeable future is more likely within a portion of the Study Area set out in the Agreement. The Committee defined this portion of the Study Area as the assessment's Focus Area. The Committee continues to conduct the Regional Assessment (i.e., present information on existing conditions and consider potential impacts of OSW) within the Focus Area. The Committee's decision to define the Focus Area and supporting rationale is available here: https://iaac-aeic.gc.ca/050/evaluations/document/153431 The Agreement to conduct the Regional Assessment is available here: https://iaac-aeic.gc.ca/050/documents/p84343/147037E.pdf
Vessel Density Mapping of 2016 AIS Data in the Northwest Atlantic
The Automatic Identification System (AIS) is a global, satellite-based and terrestrial-based ship tracking system that uses shipborne equipment to remotely track vessel identification and positional information and is typically required on vessels of 300 gross tonnage or more on an international voyage, of 500 gross tonnage or more not on an international voyage, and passenger ships of all sizes. AIS tracking technologies are primarily used in support of real-time maritime domain awareness and for maritime security and safety of life at sea. This report describes a geographic information system (GIS) analysis of 2019 AIS data to produce yearly and monthly vessel density maps of all vessel classes combined and yearly density maps of each vessel class. The year 2019 was selected to portray shipping densities in a pre-COVID 19 pandemic depiction of the maritime transport sector in the Northwest Atlantic. Vessel density map applications include use in spatial analysis and decision support for marine spatial planning. In 2023 the process was applied to the years 2013 through to 2022 and were made available using the same processes that were applied to the original 2019 datasets.
Fixed gear sentinel fisheries program - northern Gulf of St. Lawrence
In place since fall 1994, the sentinel fisheries program is the result of a collaboration between Fisheries and Oceans Canada (DFO) and Quebec and Newfoundland commercial fishermen's associations. Under this program, contracts are awarded by tender to fishermen’s associations to carry out fishing activities according to scientific protocols developed by DFO. The main objective of this survey is to collect data that will be used to calculate abundance indices for the northern Gulf of St. Lawrence Atlantic cod stock.Description of fixed gears surveyThe fixed gear sentinel fisheries of the northern Gulf of St. Lawrence are conducted in the sub-division 3Pn and the divisions 4R, 4S of the Northwest Atlantic Fisheries Organization (NAFO) using fixed gillnets or longlines (other fishing gears were also used at the start of the program). Fishing activities with nets must have a mesh size of 5 ½ inches (140mm) and are limited to a maximum of 6 to 20 nets depending on the region and capture and the target immersion time is between 19 to 24 hours. Longline fishing activities, for its part, must be carried out with traditional J #16 or C #12 hooks. The maximum number of hooks varies from 500 to 1000, depending on the catch, and the target immersion time is 4 to 6 hours. Data are collected by observers at sea or by technicians.DataFor each fishing activity, the total catch is sorted and weighed by species. For each species other than Atlantic cod, the number of individuals caught is noted. Atlantic cod are then measured at the fork (cm). Other biological data such as weight (total, gonad, liver and stomach), age, sex and maturity can then be collected on a subsample of cod.The biological data are divided into 4 files: a “Metadata” file containing set information, a “Catches” file containing catches per set for fish taxa, a “Carbio” file containing biological and morphometric measurements per individual, a “Freql” file containing the length frequency of fish.The data collected as part of this program is available below. It is important to note, however, that 1) only traits deemed successful have been retained; 2) historical data may contain inaccuracies; 3) the most recent survey is not available for validation purposes.
Removal of American eel from Port Dalhousie
In 2018 and 2019 Fisheries and Oceans Canada conducted a project to relocate American Eel (Anguilla rostrata) from Port Dalhousie Harbour to mitigate potential impacts of in-water construction prior to and during an essential harbour revitalization project. American Eel are designated as Endangered under the Province of Ontario’s Endangered Species Act and were confirmed to be present in the area during initial sampling efforts of this project. While a combination of passive eel traps and boat electrofishing were used to capture eels, this dataset includes passive capture data only. A total of four eels were captured using eel traps and all individuals were relocated to Hamilton Harbour. Only two of the four eels captured were large enough to be tagged with acoustic transmitters, both of which eventually returned to Port Dalhousie from Hamilton Harbour. All other fish species captured in the traps were identified, counted and released at Port Dalhousie.
Farm implement dealers, distributors and dealer/distributors in Ontario
This dataset contains a list of registered farm implement dealers, distributors and dealer/distributors in Ontario. Dealers offer farm implements or replacement parts for sale to the public while distributors sell, consign, or deliver farm implements or replacement parts to a dealer. Dealer/distributors carry out the function of both dealers and distributors. These dealers, distributors and dealer/distributors hold a valid registration under the [Farm Implements Act, 1990](https://www.ontario.ca/laws/statute/90f04) from the Ministry of Agriculture, Food and Agribusiness (OMAFA). The purpose of the Farm Implements Act is to improve farm machinery safety and to protect the large investments that farmers and dealers make in farm machinery. OMAFA encourages farmers and dealers to exercise caution before making investments in farm implements with a dealer or distributor who is not registered or located in Ontario. Registrations are renewed annually (expire December 31), and the list is updated annually. This list is maintained by OMAFA and includes company names, contact names and addresses.
Recreational Vessel Traffic Model for British Columbia
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.
RSQAQ - Hourly Air Quality Index (real time)
Results of the last hour available, in real time, of the [Air Quality Index (AQI)] (https://www.iqa.environnement.gouv.qc.ca/contenu/index.asp) for the stations of the [Quebec Air Quality Monitoring Network] (https://www.environnement.gouv.qc.ca/air/reseau-surveillance/Carte.asp). These results exclude those from stations located on [Montreal Island] (https://www.donneesquebec.ca/recherche/dataset/vmtl-rsqa-indice-qualite-air).The IQA is an information and awareness tool designed to inform the population about the quality of ambient air in Quebec.If you have any questions about this data, contact the Info-Air department:.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Freshwater Atlas Stream Directions
Points with rotations that indicate downstream flow direction. Can be displayed with arrow symbols to show flow direction. There is one point at the upstream end for each stream network feature
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