Pelagic Marine Ecounits are intended to describe the sea surface and water column. Two variables were selected to derive pelagic ecounits:1. Salinity and 2. Stratification. The British Columbia Marine Ecological Classification (BCMEC) is a hierarchical classification that delineates Provincial marine areas into Ecozones, Ecoprovinces, Ecoregions and Ecosections. The classification was developed from previous Federal and Provincial marine ecological classifications which were based on 1:2,000,000 scale information. The BCMEC has been developed for marine and coastal planning, resource management and a Provincial marine protected areas strategy. A new, smaller level of classification termed ecounits developed using 1:250,000 scale depth, current, exposure, subsurface relief and substrate was created to verify the larger ecosections, and to delineate their boundaries. CRIMS is a legacy dataset of BC coastal resource data that was acquired in a systematic and synoptic manner from 1979 and was intermittently updated throughout the years. Resource information was collected in nine study areas using a peer-reviewed provincial Resource Information Standards Committee consisting of DFO Fishery Officers, First Nations, and other subject matter experts. There are currently no plans to update this legacy data.

This shapefile dataset was designed using polygons extracted from the Cartography of Coastal Ecosystems of Maritime Quebec geodatabase (2022, Laboratory for Dynamics and Integrated Management of Coastal Zones, Fisheries and Oceans Canada), described in the paragraph below. It consists of polygons with eelgrass and incorporates attributes describing the vegetation cover, the composition of the seagrass beds, the associated ecosystem name, the imagery data that allowed photo-interpretation and the presence or absence of field data. A unique sequence number associated with each polygon makes it possible to trace the paired polygon of the geodatabase of coastal ecosystems to attribute values not detailed in this shapefile. The study area includes all of the estuarine and maritime coasts of Quebec, with the exception of certain sectors, including most of the Lower North Shore and Anticosti Island, with the exception of villages of Kegaska, la Romaine, Chevery, Blanc-Sablon and Port-Menier. Some islands off the estuary and gulf coasts are part of the region covered, such as Île d'Orléans, Isle-aux-Coudres, Île Verte and Île Bonaventure.The Mapping of Coastal Ecosystems of Maritime Quebec was carried out jointly by the Laboratory for Dynamics and Integrated Coastal Zone Management (LDGIZC) of the University of Quebec at Rimouski as part of the Coastal Resilience Project; and by the Fisheries and Oceans Canada team, as part of the Integrated Marine Response Planning Program (IMRP). A classification of coastal ecosystems was carried out on more than 4,200 km of coastal corridor, focusing on estuarine and maritime coasts of Quebec located between the limit of the upper foreshore and the shallow infralittoral (about 10m deep). The mapping method developed is based on semi-automated segmentation and a photo-interpretation of coastal ecosystems, using very high resolution multispectral photographs (RBVI) acquired between 2015 and 2020 by DFO. The classification of polygons is based on the assignment of predefined value classes for the biological and physical attributes under study (e.g., substrates, plant type, vegetation cover, geosystem, etc. ). Helicopter-born oblique photographs and field data helped to reduce the uncertainty associated with photo-interpretation. UQAR and DFO conducted field sampling campaigns targeting the mediolittoral (4,390 stations) and the lower mediolittoral and infralittoral zones (2,959 stations), respectively , which validated some of the attributes identified by photo-interpretation and provided detailed information on community structure . The geodatabase of the Mapping of coastal ecosystems is hosted and managed by UQAR on their SIGEC-Web cartographic platform: https://ldgizc.uqar.ca/Web/sigecwebCredits © DFO (2023, Fisheries and Oceans Canada)Provencher-Nolet, L., Paquette, L., Pitre, L.D., Grégoire, B. and Desjardins, C. 2024. Cartographie des macrophytes estuariens et marins du Québec. Rapp. Tech. Can. Sci. halieut. Aquat. 3617 : v + 99 p.Grégoire, B., Pitre, L.D., Provencher-Nolet, L., Paquette, L. and Desjardins, C. 2024. Distribution d’organismes marins de la zone côtière peu profonde du Québec recensés par imagerie sous-marine de 2017 à 2021. Rapp. tech. can. sci. halieut. aquat. 3616 : v + 78 p.Grégoire, B. 2022. Biodiversité du relevé côtier Planification pour une intervention environnementale intégrée dans l’estuaire et le golfe du Saint-Laurent (2017–2021). Observatoire global du Saint-Laurent. [Jeu de données]Jobin, A., Marquis, G., Provencher-Nolet, L., Gabaj Castrillo. M. J., Trubiano C., Drouet, M., Eustache-Létourneau, D., Drejza, S. Fraser, C. Marie, G. et P. Bernatchez (2021) Cartographie des écosystèmes côtiers du Québec maritime — Rapport méthodologique. Chaire de recherche en géoscience côtière, Laboratoire de dynamique et de gestion intégrée des zones côtières, Université du Québec à Rimouski. Rapport remis au ministère de l’Environnement et de la Lutte contre les changements climatiques, septembre 2021, 98 p.

The layer presents the information on the distribution of eelgrass (Zostera marina) beds in James Bay, Chaleur Bay, Estuary and Gulf of St. Lawrence according to a literature review of documents produced between 1987 and 2009. Additional InformationEelgrass's inventory was produced according to a literature review of the following documents:Calderón, I. 1996. Caractérisation de la végétation et de la faune ichtyenne de la baie de Sept-Îles. Document réalisé par la Corporation de protection de l'environnement de Sept-Îles pour Pêches et Océans Canada. 26p. + 5 annexes.Comité côtier Les Escoumins à la Rivière Betsiamites. 2004. Inventaire de localisation des bancs de zostère marine dans la zone côtière Les Escoumins à la rivière Betsiamites. 9 p.Comité ZIP Côte-Nord du Golfe. 2001. Inventaire du potentiel côtier et marin de la Basse-Côte-Nord. Version préliminaire de rapport sous forme de CD-ROM, Sept-Îles, mars 2001.Comité ZIP de la rive nord de l’estuaire. 2008. Guide d’intervention en matière de protection et de mise en valeur des habitats littoraux d’intérêt de la rive nord de l’estuaire maritime (fiches 14 à 20). 8 p. + 7 fiches + annexe.Conseil Régional de l’Environnement Gaspésie et des Îles-de-la-Madeleine (2004). Inventaire et étude des bancs de zostère marine sur le territoire couvert par les comités de gestion intégrée de la zone côtière de l’Est du Québec. CONSORTIUM GAUTHIER & GUILLEMETTE - G.R.E.B.E. 1992. Description et cartographie des habitats côtiers de la Baie de Hannah jusqu'à la rivière au Castor. Rapport présenté à Hydro-Québec, Complexe Nottaway-Broadback-Rupert (NBR), Vol. 2, Annexe cartographique.Giguère, M., C. Duluc, S. Brulotte, F. Hazel, S. Pereira et M. Gaudet. 2006. Inventaire d’une population d'huître américaine (Crassostrea virginica) dans le Bassin aux Huîtres aux Îles-de-la-Madeleine en 2005. Rapport manuscrit. vi + 21 p.Grant, C. et L. Provencher, 2007. Caractérisation de l’habitat et de la faune des herbiers de Zostera marina (L.) de la péninsule de Manicouagan (Québec). Rapp. tech. can. sci. halieut. aquat. 2772 : viii + 65 p. Groupe Environnement Littoral. 1992. Complexe NBR. La zostère marine. Rapport présenté à la vice-présidence Environnement d'Hydro-Québec. 9 p. + 2 cartes.Harvey, C. et D. Brouard. 1992. Étude exploratoire du barachois de Chandler: aspects biophysiques et contamination. Rapport présenté à Environnement Canada, Direction de la protection de l'environnement région du Québec. 39 p. et annexes.Hazel, François, 2002. Données de terrain prises par F. Hazel, Septembre 2002.Ellefsen, H.-F. 2009. Communication personnelle de Hans-Frédéric Ellefsen (MPO).Jacquaz et coll. 1990. Étude biophysique de l'habitat du poisson de quatre barachois de la baie des Chaleurs.Kedney, G. et P. Kaltenback. 1996. Acquisition de connaissances et mise en valeur des habitats du banc de Portneuf. Document réalisé par la firme Pro Faune pour le Comité touristique de Rivière-Portneuf. 50 pages et 5 annexes.Lalumière, R. 1987. Répartition de la zostère marine (Zostera marina) sur la côte est de la baie James; été 1987. Rapport produit par Gilles Shooner et Associés inc. pour la Société d’énergie de la Baie James. 30 p. et annexes.Lalumière, R., L. Belzile et C. Lemieux. 1992. Étude de la zostère marine le long de la côte nord-est de la baie James (été 1991). Rapport présenté au Service écologie de la SEBJ. 31 p. + carte.Leblanc, J. 2002. Communication personnelle de Judith Leblanc (MPO).Lemieux, C. 1995. Acquisition de connaissances des habitats côtiers dans la région de Rimouski (1995). Rapport du Groupe-Conseil GENIVAR présenté au Ministère des Pêches et des Océans du Canada, Division de la Gestion de l’Habitat du Poisson, 52 pages + 2 annexes.Lemieux, C. et R. Lalumière. 1995. Acquisition de connaissances des habitats côtiers du barachois de Saint-Omer. Rap. du Groupe conseil Genivar inc. pour la DGHP, MPO, 44 pages + 3 ann.Martel, Marie-Claude, Lizon Provencher, Cindy Grant, Hans-Frédéric Ellefsen et Selma Pereira, 2009. Distribution and description of eelgrassbeds in Québec. Fisheries and Oceans Canada, Canadian Science Advisory Secretariat, Research Document 2009/050. 45p. Morin, D. 2009. Communication personnelle de Danièle Morin (MRNF).Naturam Environnement. 1999. Caractérisation biophysique, socio-économique et détermination des enjeux dans un secteur potentiel pour l’identification d’une zone de protection marine pilote: portion ouest de la MRC Manicouagan. Baie-Comeau. 311 p. Pelletier, Claudel. 2003. Communication personnelle de Claudel Pelletier, FAPAQ, lettre en date du 24 février 2003.Pereira, S. 2009. Communication personnelle de Selma Pereira (MPO).Vaillancourt, M.-A. et C. Lafontaine. 1999. Caractérisation de la Baie Mitis. Jardins de Métis et Pêches et Océans Canada. Grand-Métis. 185 p.

Marine classification schemes based on abiotic surrogates often inform regional marine conservation planning in lieu of detailed biological data. However, theses chemes may poorly represent ecologically relevant biological patterns required for effective design and management strategies. We used a community-level modeling approach to characterize and delineate representative mesoscale (tens to thousands of kilometers) assemblages of demersal fish and benthic invertebrates in the North-west Atlantic. Hierarchical clustering of species occurrence data from four regional annual multispecies trawl surveys revealed three to six groupings (predominant assemblage types) in each survey region, broadly associated with geomorphic and oceanographic features. Indicator analyses identified 3–34 emblematic taxa of each assemblage type. Random forest classifications accurately predicted assemblage dis-tributions from environmental covariates (AUC > 0.95) and identified thermal limits (annual minimum and maximum bottom temperatures) as important pre-dictors of distribution in each region. Using forecasted oceanographic conditions for the year 2075 and a regional classification model, we projected assemblage dis-tributions in the southernmost bioregion (Scotian Shelf-Bay of Fundy) under ahigh emissions climate scenario (RCP 8.5). Range expansions to the north eastare projected for assemblages associated with warmer and shallower waters of the Western Scotian Shelf over the 21st century as thermal habitat on the rela-tively cooler Eastern Scotian Shelf becomes more favorable. Community-level modeling provides a biotic-informed approach for identifying broadscale ecolog-ical structure required for the design and management of ecologically coherent, representative, well-connected networks of Marine Protected Areas. When com-bined with oceanographic forecasts, this modeling approach provides a spatial tool for assessing sensitivity and resilience to climate change, which can improve conservation planning, monitoring, and adaptive management.Cite this data as: O'Brien, J.M., Stanley, R.R.E., Jeffery, N.W., Heaslip, S.W., DiBacco, C., and Wang, Z. Demersal fish and benthic invertebrate assemblages in the Northwest Atlantic.Published: December 2024. Coastal Ecosystems Science Division, Maritimes region, Fisheries and Oceans Canada, Dartmouth NS.https://open.canada.ca/data/en/dataset/14d55ea5-b17d-478c-b9ee-6a7c04439d2b

Benthic Marine Ecounits in coastal and offshore British Columbia. Benthic ecounits are intended to describe the sea bed and nearshore. Seven variables were selected to derive benthic ecounits: 1. Depth; 2. Slope; 3. Relief; 4. Temperature; 5. Exposure; 6. Current and 7. Substrate. CRIMS is a legacy dataset of BC coastal resource data that was acquired in a systematic and synoptic manner from 1979 and was intermittently updated throughout the years. Resource information was collected in nine study areas using a peer-reviewed provincial Resource Information Standards Committee consisting of DFO Fishery Officers, First Nations, and other subject matter experts. There are currently no plans to update this legacy data.

Since 2005, Fisheries and Oceans Canada has been collecting monitoring data for aquatic invasive species (e.g. https://open.canada.ca/data/en/dataset/8d87f574-0661-40a0-822f-e9eabc35780d, https://open.canada.ca/data/en/dataset/503a957e-7d6b-11e9-aef3-f48c505b2a29, https://open.canada.ca/data/en/dataset/8661edcf-f525-4758-a051-cb3fc8c74423). This monitoring data, as well additional occurrence information from online databases and the scientific literature, have been paired with high resolution environmental data and oceanographic models in species distribution models that predict the present-day and future potential distributions of 12 moderate to high risk invasive species on Canada’s east and west coasts. Future distributions were predicted for 2075, under Representative Concentration Pathway 8.5 from the Intergovernmental Panel on Climate Change’s fifth Assessment Report. Present-day and future richness of these species (i.e., hotspots) has also been estimated by summing their occurrence probabilities. This data set includes the occurrence locations of each species, the present-day and future species distribution modeling results for each species, and the estimated species richness. This research has been published in the scientific literature(Lyons et al. 2020).Lyons DA, Lowen JB, Therriault TW, Brickman D, Guo L, Moore AM, Peña MA, Wang Z, DiBacco C. (In Press) Identifying Marine Invasion Hotspots Using Stacked Species Distribution Models. Biological InvasionsCite this data as: Lyons DA., Lowen JB, Therriault TW., Brickman D., Guo L., Moore AM., Peña MA., Wang Z., DiBacco C. Data of: Species distribution models and occurrence data for marine invasive species hotspot identification. Published: November 2020. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/1bbd5131-8b34-4245-b999-3b4c4259d74f

Funded under DFO's Marine Conservation Targets Program in partnership with the Huntsman Marine Science Centre (HMSC), this diver-based imagery and sample collection benthic survey documents the occurrence of sponges at 42 dive sites in the Eastern Shore Islands (ESI) Area of Interest (AOI, ~2089 km2) off the Atlantic coast of Nova Scotia, Canada from dive surveys conducted in summer 2021 and 2022. Water quality, species occurrences and counts, habitat, slope, and substrate characteristics were catalogued through diver log sheets, camera imagery, specimen vouchers, and high-resolution bathymetric data. A total of 54 dives to depths from 11 to 33 m (below sea level), collecting up to 147 still images, one-hour of video, and 17 specimen samples per site, resulted in 220 observations for 27 different sponge taxa. This included three new records for Canada (Hymedesmia stellifera, Plocamionida arndti, Hymedesmia jecusculum) and a range extension for a species new to science (Crellomima mehqisinpekonuta) which was recently described from the Bay of Fundy. There were also four species which may seem to be new to science (Halichondria sp., Hymedesmia sp., Protosuberires sp., and Sphaerotylus sp.). Sponges were found to occupy a diversity of micro-habitats, often several different ones in proximity. A total of eight distinct habitat classes were defined, based on varying abundances and diversity of sponges and associated benthic species. These are likely widely distributed among the many complex submerged seabed features within this AOI. Collected specimens were preserved and are stored at the Atlantic Reference Centre (ARC) in St. Andrew's, New Brunswick.Cite this data as: Goodwin, C., Cooper, J.A., Lawton, P., Teed, L.L. 2025. Sponge occurrence and associated species and habitat descriptions derived from the 2021 and 2022 SCUBA diving surveys in the Eastern Shore Islands Area of Interest, Nova Scotia. Version 1.4. Fisheries and Oceans Canada. Occurrence dataset. https://ipt.iobis.org/obiscanada/resource?r=eastern_shore_islands_sponge_survey_2021_2022&v=1.4

Nekton assemblages in Zostera marina beds and adjacent bare soft-sediments were sampled on the south and eastern shore of Nova Scotia. Sampling gear used were visual snorkel transects and a benthic beam trawl. Fish were identified and size either measured (trawl) or estimated in situ (snorkel transects). Surveys were conducted in mid-July to Aug in summer of 2013 and 2014 across multiple sampling sites. Multiple replicate transects were conducted at each site. Raw abundances from observations were transformed into young of year (YOY) equivalent abundance, and then into density of each species calibrated to account for the sampling equipment and day/night differences.Cite this data as: Wong, M. C. Data of: Fish and large decapods in eelgrass (Zostera marina) beds on the Atlantic coast of Nova Scotia, Canada. Published: April 2020. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/dbc56f11-4a97-45e7-99f4-71966b51630c

Eelgrass (Zostera marina) is important to waterfowl such as Atlantic Brant (Branta bernicla hrota), Canada Goose (Branta canadensis), American Black Duck (Anas rubripes), Common Goldeneye (Bucephala clangula) and Barrow's Goldeneye (Bucephala islandica). In New Brunswick eelgrass can be found along the Gulf of St. Lawrence, in protected harbours. Within this dataset are the results eelgrass land-cover classifications using either satellite or aerial photography for eight harbours: Bouctouche (46 30’N, 64 39’W); Cocagne (46.37 N, -64.60 W); Miscou (47.90 N, -64.55 W); Neguac (47.25 N, -65.03 W); Richibucto (46.70 N, -64.80 W); Saint-Simon (47.77 N, -64.76 W); Tabusintac (47.33 N, -64.93 W); and Tracadie (47.55 N, -64.88 W). Information on each dataset is provided:Visible orthorectified aerial photography was used to classify polygons containing eelgrass in Cocagne Harbour. Field data for image training and validation were collected along transects in summer 2008 using a dGPS positioned towfish holding sidescan sonar and a video camera that was later transcribed as XY geographic points to describe eelgrass presence and a qualitative description of density. The area was flown for photography on September 24, 2008. eCognition Developer 8 software was used to segment the imagery, essentially polygons. Polygons were then classified manually for the presence of eelgrass. Using field data revealed eelgrass presence to be mapped correctly 87.2% of the time.

Eelgrass (Zostera marina) is important to waterfowl such as Atlantic Brant (Branta bernicla hrota), Canada Goose (Branta canadensis), American Black Duck (Anas rubripes), Common Goldeneye (Bucephala clangula) and Barrow's Goldeneye (Bucephala islandica). In New Brunswick eelgrass can be found along the Gulf of St. Lawrence, in protected harbours. Within this dataset are the results of eelgrass land-cover classifications using either satellite or aerial photography for seven harbours: Bouctouche (46 30’N, 64 39’W); Miscou (47.90 N, -64.55 W); Neguac (47.25 N, -65.03 W); Richibucto (46.70 N, -64.80 W); Saint-Simon (47.77 N, -64.76 W); Tracadie (47.55 N, -64.88 W); and Cocagne (46.370 N, -64.600 W). Information on each dataset is provided:1. BouctoucheThis 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].2. MiscouTrue colour aerial photography at 57 centimetre resolution was collected on August 20th and 24th, 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 103 sites. From these sites 70% 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 96.7% of the time (30/31 = 0.967). 3. NeguacThis dataset contains results from an eelgrass classification for Neguac 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 126 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 81% 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 39 sites that were within the classification area, 27 were correct, 9 were "one-off", and 3 were incorrect [(27 + (9/2))/ 39 = 0.81].4. RichibuctoEelgrass classification in Richibucto Harbour, New Brunswick. Derived from a Quickbird satellite image collected on August 28, 2007 at as close to low-tide as possible. Quickbird's ground resolution is 2.4 m. Classification was objected-oriented using Definiens software. Accuracy was 81.5%. Data used for accuracy and training was collected along transects using a differential GPS positioned towfish holding sidescan sonar, and a video camera that was later transcribed as XY points to describe eel-grass presence.5. Saint-SimonAn eelgrass distribution map was classified from remotely sensed imagery in Shippagan Harbour, New Brunswick. Derived from a Quickbird satellite image collected on July 27, 2007 at as close to low-tide as possible. Classification was objected-oriented using Definiens software. Data used for accuracy and training was collected along transects using a differential GPS positioned towfish holding sidescan sonar, and a video camera that was later transcribed as XY points to describe eel-grass presence.6. TracadieThis dataset contains results from an eelgrass classification for Tracadie 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 101 sites. Approximately two-thirds of these sites were used to assist in image classification, while the remainder was 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 79.3% 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 29 sites that were within the classification area, 18 were correct, 10 were "one-off", and 1 was incorrect [(18 + (10/2))/ 29 = 0.793].7. CocagneVisible orthorectified aerial photography was used to classify polygons containing eelgrass in Cocagne Harbour. Field data for image training and validation were collected along transects in summer 2008 using a dGPS positioned towfish holding sidescan sonar and a video camera that was later transcribed as XY geographic points to describe eelgrass presence and a qualitative description of density. The area was flown for photography on September 24, 2008. eCognition Developer 8 software was used to segment the imagery, essentially polygons. Polygons were then classified manually for the presence of eelgrass. Using field data revealed eelgrass presence to be mapped correctly 87.2% of the time.