Monthly mean currents from Bedford Institute of Oceanography North Atlantic Model (BNAM) results were averaged over 1990 to 2015 period to create monthly mean climatology for the Northwest Atlantic Ocean, which can be considered as a representation of the climatological state of the Northwest Atlantic Ocean. The BNAM model is eddy-resolving, NEMO-based ice-ocean coupled North Atlantic Ocean model developed at the Bedford Institute of Oceanography (BIO) to support DFO monitoring programs. The data available here is monthly climatology for eight selected depths (surface, 110 m, 156 m, 222 m, 318 m, 541 m, 1062 m, bottom) in 1/12 degree spatial resolution. The data for each month from 1990 until present for the entire model domain ( 8°–75°N latitude and 100°W–30°E longitude) and various depths is available upon request. The 1990-2017 model hindcast result is compared with observational data from surface drifter and satellite altimetry. The model demonstrates good skill in simulating surface currents, winter convection events in the Labrador Sea, and the Atlantic Meridional Overturning Circulation as observed at 26.5°N and 41°N. Model results have been used to interpret changes in the Labrador Current and observed warming events on the Scotian Shelf, and are reported through the annual AZMP Canadian Science Advisory Secretariat Process. When using data please cite following: Wang, Z., Lu, Y., Greenan, B., Brickman, D., and DeTracey, B., 2018. BNAM: An eddy resolving North Atlantic Ocean model to support ocean monitoring. Can. Tech. Rep. Hydrogr. Ocean. Sci. 327: vii + 18p

Shorelines for the Pasqua, Crooked, Echo, and Round Lakes within the Qu'Appelle Valley River system in Saskatchewan

The proportion of agricultural land as percentage of Soil Landscape of Canada (SLC) polygon area data set depicts areas of greater than 2% of agriculture within agricultural extents of Canada.

The Department of Fisheries established a survey of demersal juvenile Atlantic cod (*Gadus morhua*) in the nearshore (<10 m deep) in 1959. This survey aimed to characterize the distribution and abundance of juvenile Atlantic cod and was based upon Norway's Flodevigen sampling program which has been conducted continuously since 1919. A 25 m seine was used to sample juvenile Atlantic cod nursery locations on the Avalon Peninsula and Northeast coast of the island of Newfoundland in September and October. The survey continued until 1964 and became known as the Fleming survey, after original initiator Alistair Fleming. The survey was reinstated by Memorial University of Newfoundland from 1992 to 1997. Multiple tows were conducted at a subset of the original 55 Fleming sites located in St. Mary's Bay, Trepassey Bay, the Southern Shore, Conception Bay, Trinity Bay, Bonavista Bay, Gander Bay, New World Island, Fortune Harbour, Badger Bay, Halls Bay and Green Bay. This data set includes several different subsets, some of which span both Fleming Survey periods (1959-1964 and 1992-1997): I. JuvCodCatch60s90s: Catches of juvenile Atlantic cod (1959-1964, 1992-1997) from the first two consecutive tows at each site. This is a summary based on JuvCodLengths90s and FlemingSurveyData60s; II. JuvCodLength90s: Lengths of all individual juvenile Atlantic cod caught for each site (1992-1997); III. SiteEnvData60s90s: Station data for Fleming data 1992-1997; IV. FlemingSurveyData60s: Fleming survey data from 1959-1964 (note there are three record types pertaining to: station data "type 1"; general species catch data including juvenile Atlantic cod grouped by age class ("1+", "Zeroes", and "Total") "type 2; and juvenile Atlantic cod (species 223) listed in length bins "type 3"; and V. FlemingBycatch60s92to96: Bycatch data from 1959-1964 & 1992-1996 from first two tows at each site. This is a summary based partly on the FlemingSurveyData60s set.

The National Pedon Database is a limited, vetted dataset containing over a hundred soil properties. Additionally, this release of the National Pedon Database is only a subset of the information contained within the core National Pedon Database (NPDB) holdings.

This dataset contains results from an eelgrass classification for Bouctouche Bay, New Brunswick. True colour aerial photography at 57 centimetre resolution was collected on September 2, 2009 by Nortek Resources of Thorburn, Nova Scotia (http://www.nortekresources.com/). Image classification was conducted using eCognition Developer v. 8 Software, which first segments the image into spectrally similar units, which were then classified manually. Additionally, the Department of Fisheries and Oceans (Gulf Region, Moncton, NB) conducted a visual field survey in the same field season at 688 sites. Two-thirds of these sites were used to assist in image classification, while the remainder were used to assess accuracy. Three classes were identified: i. Good Quality Eelgrass: relatively dense, clean, green blades with minimal epiphytes or algal growth. ii. Medium Quality Eelgrass: predominately green blades that may have some epiphyte or algal growth. These stands can be less or equally dense as Good Quality Eelgrass, but the best grasses are certainly not as abundant. iii. Eelgrass Absent/Poor Quality: eelgrass is absent, or if it is present it is typically covered with epiphytes or other algae or dying or dead. Eelgrass was classified correctly 83.7% of the time in a fuzzy accuracy assessment technique, whereby those classes that were ‘off’ by one class, e.g. Good Quality eelgrass classed as Medium Quality, were given half credit towards the overall accuracy. Of 187 sites that were within the classification area, 131 were correct, 51 were "one-off", and 5 were incorrect [(131 + (51/2))/ 187 = 0.837].

Bay Scale Assessment of Nearshore Habitat Bras dOr Lake - Malagawash 2007 2008 data is part of the publication Bay Scale Assessment of Nearshore Habitat Bras d'Or Lakes. A history of nearshore benthic surveys of Bras d’Or Lake from 2005 – 2011 is presented. Early work utilized drop camera and fixed mount sidescan. The next phase was one of towfish development, where camera and sidescan were placed on one platform with transponder-based positioning. From 2009 to 2011 the new towfish was used to ground truth an echosounder. The surveys were performed primarily in the northern half of the lake; from 10 m depth right into the shallows at less than 1 m. Different shorelines could be distinguished from others based upon the relative proportions of substrate types and macrophyte canopy. The vast majority of macrophytes occurred within the first 3 m of depth. This zone was dominated by a thin but consistent cover of eelgrass (Zostera marina L.) on almost all shores with a current or wave regime conducive to the growth of this plant. However, the eelgrass beds were frequently in poor shape and the negative impacts of commonly occurring water column turbidity, siltation, or possible localized eutrophication, are suspected. All survey data were placed into a Geographic Information System, and this document is a guide to that package. The Geographic Information System could be used to answer management questions such as the placement and character of habitat compensation projects, the selection of nearshore protected areas or as a baseline to determine long term changes. Vandermeulen, H. 2016. Video-sidescan and echosounder surveys of nearshore Bras d’Or Lake. Can. Tech. Rep. Fish. Aquat. Sci. 3183: viii + 39 p. Cite this data as: Vandermeulen H. Bay Scale Assessment of Nearshore Habitat Bras d'Or Lake - Malagawash 2007 - 2008. Published May 2022. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.

A history of nearshore benthic surveys of Bras d’Or Lake from 2005 – 2011 is presented. Early work utilized drop camera and fixed mount sidescan. The next phase was one of towfish development, where camera and sidescan were placed on one platform with transponder-based positioning. From 2009 to 2011 the new towfish was used to ground truth an echosounder. The surveys were performed primarily in the northern half of the lake; from 10 m depth right into the shallows at less than 1 m. Different shorelines could be distinguished from others based upon the relative proportions of substrate types and macrophyte canopy. The vast majority of macrophytes occurred within the first 3 m of depth. This zone was dominated by a thin but consistent cover of eelgrass (Zostera marina L.) on almost all shores with a current or wave regime conducive to the growth of this plant. However, the eelgrass beds were frequently in poor shape and the negative impacts of commonly occurring water column turbidity, siltation, or possible localized eutrophication, are suspected. All survey data were placed into a Geographic Information System, and this document is a guide to that package. The Geographic Information System could be used to answer management questions such as the placement and character of habitat compensation projects, the selection of nearshore protected areas or as a baseline to determine long term changes. Vandermeulen, H. 2016. Video-sidescan and echosounder surveys of nearshore Bras d’Or Lake. Can. Tech. Rep. Fish. Aquat. Sci. 3183: viii + 39 p. Cite this data as: Vandermeulen H. Bay Scale Assessment of Nearshore Habitat Bras d'Or Lake. Published May 2022. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S.

This data represents the Ministry of Natural Resources (MNR) administrative boundaries from 1997-2022. Ministry of Natural Resources (MNR) administrative areas divide Ontario into smaller organizational units. These units were used to manage ministry programs and resources at a district and regional level. Regional and district boundaries were originally created based on: * metes and bounds * topographic features * geographic townships boundaries * territorial district boundaries We made changes to district boundaries over time. We are no longer updating this data. It is best suited for historical research and analysis. __MNR regions__ MNR regions were created to help manage ministry programs and resources at a regional level. Regions consist of several districts. __MNR districts__ MNR regions were divided into smaller organizational units called districts. __MNR areas__ MNR districts were further divided into areas.

The 1 cm resolution vegetation digital height model was extracted using a bare earth model and digital surface model (DSM) derived from unmanned aerial vehicle (UAV) imagery acquired from a single day survey on July 28th 2016, in Cambridge Bay, Nunavut. The mapping product covers 525m2 and was produced by Canada Centre for Remote Sensing /Canada Centre for Mapping and Earth Observation. The UAV survey was completed in collaboration with the Canadian High Arctic Research Station (CHARS) for northern vegetation monitoring research. For more information, refer to our current Arctic vegetation research: Fraser et al; "UAV photogrammetry for mapping vegetation in the low-Arctic" Arctic Science, 2016, 2(3): 79-102. http://www.nrcresearchpress.com/doi/abs/10.1139/AS-2016-0008