A derived analysis from Department of Fisheries and Oceans Canada near-seafloor optical imagery survey for the St. Anns Bank Marine Protected Area, this dataset is based on a subset of 639 high-resolution digital still images of the seafloor using a Nikon D850 camera during an imagery survey from 2023 and 2024. This dataset documents the presence of all visible taxa to the lowest taxonomic level, as well as general habitat descriptions of each transect. Images were analyzed for taxa and morphotype occurrences using the image annotation software BIIGLE (https://biigle.de/), resulting in 15586 occurrences for ~240 different taxa and/or morphotypes. Morphotype descriptions and suggested/likely taxa are provided under "occurrenceRemarks". An annotation guide describing each taxa and morphotype is provided as an appendix in the associated technical report (Teed et al. 2025). Sponges were the most commonly occurring phyla (namely encrusting morphotypes), followed by enchinoderms and chordates (i.e., ascidians). Commonly occurring taxa include Serpulid worms, encrusting bryozoans, Celleporina spp. and Caberea ellisii bryozoans, Leptothecata hydrozoans, sea stars (Asterias spp. and/or Leptasterias spp.), daisy brittle stars (Ophiopholis aculeata), orange encrusting sponges, and encrusting coralline algae (Boreolithothamnion glaciale).
","language":"eng","homepage":"https://open.canada.ca/data/en/dataset/2a55e2b4-cbb6-4fea-b17e-a16f5e99e68f","citation":{"text":"Teed L, Lawton P (2026). Taxa occurrences from a near-seafloor optical imagery survey conducted in 2023 and 2024 in the St. Anns Bank Marine Protected Area, Nova Scotia, Canada. Fisheries and Oceans Canada. Sampling event dataset https://doi.org/10.15468/vghhk9 accessed via GBIF.org on 2026-10-29.","citationProvidedBySource":false},"contactsCitation":[{"key":6964398,"abbreviatedName":"Teed L","firstName":"Laura","lastName":"Teed","roles":["METADATA_AUTHOR","ORIGINATOR"],"userId":[]},{"key":6964400,"abbreviatedName":"Lawton P","firstName":"Peter","lastName":"Lawton","roles":["METADATA_AUTHOR"],"userId":[]}],"lockedForAutoUpdate":false,"createdBy":"c98a8d0d-cab2-4506-8c0f-c91a5e4996b9","modifiedBy":"crawler.gbif.org","created":"2026-03-30T14:50:01.836+00:00","modified":"2026-03-30T14:51:02.951+00:00","contacts":[{"key":6964398,"type":"ORIGINATOR","primary":true,"userId":[],"firstName":"Laura","lastName":"Teed","position":["Aquatic Science Biologist"],"email":["laura.teed@dfo-mpo.gc.ca"],"phone":[],"homepage":[],"organization":"Fisheries and Oceans Canada","address":["125 Marine Science Drive"],"city":"Saint Andrew's","province":"New 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Anns Bank Marine Protected Area, Cape Breton, Nova Scotia, Canada","boundingBox":{"minLatitude":45.823602,"maxLatitude":46.143792,"minLongitude":-60.074618,"maxLongitude":-58.837315,"globalCoverage":false}}],"temporalCoverages":[{"@type":"range","start":"2023-08-15T00:00:00.000+00:00","end":"2024-08-17T00:00:00.000+00:00"}],"keywordCollections":[{"thesaurus":"GBIF Dataset Type Vocabulary: http://rs.gbif.org/vocabulary/gbif/dataset_type_2015-07-10.xml","keywords":["Samplingevent\nOccurrence"]},{"thesaurus":"GBIF Dataset Subtype Vocabulary: http://rs.gbif.org/vocabulary/gbif/dataset_subtype.xml","keywords":["Observation"]}],"project":{"title":"Coastal seabed habitat inventory and biodiversity assessment in support of bioregional conservation network planning and development of MPA monitoring programs","identifier":"691","contacts":[{"type":"PRINCIPAL_INVESTIGATOR","primary":false,"userId":[],"firstName":"Laura","lastName":"Teed","position":[],"email":[],"phone":[],"homepage":[],"address":[]},{"type":"PRINCIPAL_INVESTIGATOR","primary":false,"userId":[],"firstName":"Peter","lastName":"Lawton","position":[],"email":[],"phone":[],"homepage":[],"address":[]},{"type":"PRINCIPAL_INVESTIGATOR","primary":false,"userId":[],"firstName":"Ryan","lastName":"Stanley","position":[],"email":[],"phone":[],"homepage":[],"address":[]},{"type":"PRINCIPAL_INVESTIGATOR","primary":false,"userId":[],"firstName":"Nick","lastName":"Jeffery","position":[],"email":[],"phone":[],"homepage":[],"address":[]},{"type":"PRINCIPAL_INVESTIGATOR","primary":false,"userId":[],"firstName":"Javier","lastName":"Murillo","position":[],"email":[],"phone":[],"homepage":[],"address":[]}],"funding":"This research was funded by the Department of Fisheries and Oceans Canada as part of the Marine Conservation Targets Program under the Maritimes Region project number 691.","awards":[],"studyAreaDescription":"St. Anns Bank Marine Protected Area, Nova Scotia, Canada","designDescription":"For full design and detailed technical reports see: https://open.canada.ca/data/en/dataset/2a55e2b4-cbb6-4fea-b17e-a16f5e99e68f","relatedProjects":[],"abstract":"Using a newly developed near-seafloor optical imaging system (capable at surveying depths up to 200-m) to support conservation network planning and development of MPA monitoring programs"},"samplingDescription":{"studyExtent":"St. Anns Bank Marine Protected Area, Cape Breton, Nova Scotia, Canada","sampling":"SITE SELECTION AND SURVEY PLANNING\nIn the St. Anns Bank MPA, benthic imagery was obtained at 41 locations during five day trips in August 2023 (11 day overall survey window) and a further five day trips in August 2024 (12 day overall survey window), using the FOBIS near-seafloor optical imaging system operating off the CCGS M. Perley. Survey target locations in 2023 were chosen using high-resolution (5-35-m spatial resolution) multibeam echosounder bathymetry data acquired from the Canadian Hydrographic Service (CHS), visualized in ArcGIS Pro v.2.8 (ESRI 2021). More specifically, high-resolution multibeam data was used to identify unique bathymetric features including Scatarie and Curdo Banks and subsequently choose target survey locations. There are only a few locations within the MPA where shallow bathymetry (e.g. less than 30 m) can potentially be effectively surveyed using SCUBA diving approaches. Preliminary acquisition of benthic imagery using surface-deployed cameras in these areas was additionally intended to provide planning context for developing future dive survey efforts. Other target locations were selected to overlap with prior scientific benthic survey effort within the MPA to provide for potential assessment of changes in community assemblages. These prior surveys included benthic trawl set locations from the RV Survey from 2017-2019 (2023 and 2024 locations were not yet available when planning the survey), and benthic imagery surveys from 2009-2010 and 2015 and 2013-2014. \nSpecific locations were also chosen to further ground-truth unique benthoscape classifications previously defined by Lacharité et al. (2018). Benthoscape classifications aim to identify discrete regions of the seafloor based on biophysical characteristics including the combination of substrate type, biological structures and general topography estimated by acoustic techniques (Brown et al. 2011). In Lacharité et al. (2018), seven unique benthoscapes were identified using the ground-truthing images collected at 61 stations throughout the MPA and object-based image analysis (see Lacharité et al. 2018 for details) was used to build a benthoscape map using eCognition at a 50-m spatial resolution. Imagery for the 61 stations were collated from surveys occurring in 2009, 2010, and 2013-2015 using various benthic imaging systems operating from different large research vessels. Benthoscape classes defined by Lacharité et al. (2018) include: ‘Mud’, ‘Mud with seapens’, ‘Gravelly sand/mud with <50% cobbles/gravel’, ‘Glacial till with >50% cobbles/gravel’, ‘Glacial till with coralline algae’, ‘Gravel with crinoids’, and ‘Sand with sand dollars’. This object-based image approach was applied to bathymetry and backscatter layers (along with derivatives such as slope and Bathymetric Position Index – BPI) at a 50-m resolution, and merged image-objects to identify areas of high homogeneity and heterogeneity. Final classification was performed using a nearest neighbor supervised scheme (Lacharité et al. 2018). Based on the comprehensive design and outcomes in our 2023 survey, the 2024 survey design was adapted to aim for better balance in the range of benthoscapes surveyed, as well as to further investigate attributes of specific habitats, including shallow banks and crinoid beds. \nDuring the survey design phase, once target locations were selected, a 500-m buffer was created around each location using the buffer tool in ArcGIS Pro v.2.8 (ESRI 2021). During at-sea operations, a field laptop computer running ArcGIS and tracking the survey vessel GPS position, was used to evaluate the likely vessel drift direction prior to deployment, selecting a start location along the exterior of the buffer line to drift towards the survey target location. Preferred drift directions were pre-identified at some target locations to guide alignment of the drift survey direction over or adjacent to prior survey track lines, unique bathymetric features, or to sample specific predicted benthoscape areas.\nIn this report, recorded depths (in m Below Chart Datum – BCD) correspond to the depth below the sea surface of the FOBIS system equipped with a SBE39plus temperature and depth sensor (Sea-Bird Scientific; Bellevue, Washington, USA) referenced against tidal data from the Louisbourg station in Cape Breton, Nova Scotia (00600; https://tides.gc.ca/en/stations/00600/). Reported depths refer to the total depth; i.e., the summation of the depth sensor reading and the altitude of the camera package off-bottom \nat every survey location, adjusted according to tide. Depth sensor data was used because very high-resolution bathymetry data (1-m resolution) is not yet available for St. Anns Bank. When depth sensor data was not recorded (due to issues in the field), depths were extracted from the highest-resolution bathymetry available (5-35 m resolution).\n\nNEAR-SEAFLOOR OPTICAL IMAGERY SURVEY APPROACHES\nAt each target location surveyed, the FOBIS near-seafloor optical imaging camera system was lowered to within 2 m of the seafloor, with a maximum allowable depth deployment of 200 m. Surveys were conducted using a drift transect protocol, for a target 20 to 40-minute deployment time at each location. During the at-sea survey, a laptop computer running GIS displayed both the target location and 500-m buffers while also tracking both vessel and camera package location. The camera system provided three primary digital imagery sources. A full frame digital camera (D850, Nikon, Mississauga, ON, Canada), oriented downwards, captured individual digital still images (approx. 25 MB each) at periodic intervals (with a target of 30-s intervals, dependent on speed over ground). Digital still images were transmitted over the optical cable to the surface control system for near real-time viewing and file storage. Nikon Camera Control Pro 2 software (Nikon, Mississauga, ON, Canada) allowed for remote control of the D850 camera, enabling camera setting adjustments dependent on general marine conditions at target locations (i.e., deployment depth, type of substrate, water turbidity, altitude off bottom, etc.). Primary image settings (ISO speed, aperture, focusing mode – stored in each image file’s metadata) were generally set at the start of survey operations, and not continually adjusted. In the 2023 transects (CON11-20 and CON23-28) after some initial adjustments (from CON11-14), the focal length was set to 24 mm; focus was set to Auto; ISO speed to 800; shutter speed to 1/250 s, and the aperture to f13. Based on assessment of camera performance in the 2023 survey, Nikon camera settings for the 2024 transects (CON53-59 and CON62-79) were changed somewhat to a focal length of 25 mm; Auto focus; 800 ISO speed (except 1000 for CON73); 1/200 s shutter speed; and f14 aperture. A downward-facing high-definition video camera (1Cam Mk6, SubC Imaging, Clarenville, NL, Canada) set to Auto focus, IRIS and white balance, along with a shutter speed of 1/500 s and AE shift of -2.0 EV, and a forward-facing high-definition video camera (HD Multi SeaCam, Deep Sea Power & Light, San Diego, CA, USA) provided continuous video imagery of the seafloor. The forward-facing video imagery, along with telemetry from an altimeter on the camera frame, allowed for the FOBIS system operator on the vessel to make real-time adjustment of the camera height above the sea floor using a joy-stick controlling the deck slip-ring winch. Due to limited video channels on the FOBIS system underwater multiplexer, the forward-facing camera only transmitted composite (standard-definition) video to the surface in the configuration used in 2023 and 2024. Video files were captured in mp4 format, automatically subdivided into 10-min file durations (approx. 3.7 GB for downward video; 2.1 GB for forward video). \nBoth video and still image files were recorded and automatically named according to transect number (CON###), date and UTC time (e.g., CON011-20230815T144755). Transect CON numbers refer to a consecutive numbering system for documenting survey operations using the FOBIS system (i.e., a single numbering sequence across all system users, and survey areas over time; adopted to facilitate creation of overviews of system operations). A VA500 altimeter (Teledyne Valeport Ltd, Totnes, UK) provided records of the height of the survey package off-bottom (once every second), and a pair of lasers (10-cm spacing) provided a means to evaluate the field of view in both the downward digital video and digital still imagery (estimated using ImageJ2). For the downward-facing video, 10-cm lasers were in view when the altitude off-bottom ranged from 0.5 to 2.7 m, while the digital stills were much more restricted with field of view calculations possible when altitudes were 0.7 to 1.7 m. To generate an estimate of area covered (m2) for each transect, the average field of view from the downward-facing video across each transect was multiplied by the estimated distance travelled. These estimates were then summed across transects to generate overall seafloor area coverage. \n One still image was selected every 50 m along each transect, using buffer tools in ArcGIS Pro v.2.8 (ESRI 2021), to provide a sub-set of still images to annotate the presence of organisms. Organism occurrences in selected still images were analyzed using the image annotation software BIIGLE (Langenkamper et al. 2017) with detailed methodology described in a separate imagery annotation report (Teed et al. in press). In this report, we provide qualitative observations across transects of substrates and habitat descriptions derived from viewing a combination of video (forward- and downward-facing) and still images. Additionally, the benthoscape class of each still image was noted, using criteria established by Lacharité et al. (2018) to ground-truth their predictions: A - Mud, B - Gravelly sand/mud with <50% cobbles/gravel, C - Till with >50% cobbles/gravel, D - Till with coralline algae, E - Gravel with crinoids, and F - Sand with sand dollars (Figure 6). Each transect was assigned an overall benthoscape class based on the highest represented benthoscape across all images in a transect (i.e., the primary benthoscape). \nFor year one (2023) of the survey, an available underwater ultra-short baseline acoustic positioning system was used (Tracklink 1500HA transceiver with Tracklink 1505B transponder; Linkquest Inc., San Diego, USA); however, it proved not to be fully reliable (i.e., intermittent issues in starting up the Tracklink system or the receiver showing camera package positions ‘jumping’ around to far distances), and so in 2023, survey vessel geographic positions were recorded using a SeaNav 300 Global Navigation Satellite System receiver at the surface (Kongsberg Gruppen ASA, Kirkegårdsveien, Norway). The track line of each transect can be expected to correspond to the actual distance travelled by the camera package over the seafloor, although the offset of the camera system from the vessel was not defined. In year two (2024) of the survey, a new underwater acoustic positioning system was implemented on the survey vessel, based on the uPAP 201-H transceiver/transducer, along with cNODE Micro transponders/beacons from Kongsberg (Kongsberg Gruppen ASA, Kirkegårdsveien, Norway) allowing for transects to be mapped according to the camera system position. Year two also allowed for direct comparison of the camera system position in relation to the vessel’s position, where it was found that spatial offsets from the survey vessel ranged up to 50 m astern and 1-10 m port or starboard depending on depth and tidal influences. \nDrift camera tracks for all transects were plotted in ArcGIS Pro v.2.8 corresponding to the date and time when the camera package was in a near-seafloor survey mode. The actual distance traveled (m) by the camera package over the seafloor was calculated using the z-field geometry tool in ArcGIS Pro v.2.8 (ESRI 2021), calculated for each transect. \nOnce transect and affiliated image positions were obtained and imported into ArcGIS Pro v.2.8, a proximity analysis, using the Near (Analysis) tool (ESRI 2021) was performed to determine the shortest distance (in m) that the 2023 and 2024 still images were away from prior survey locations (including imagery surveys and RV transect sets: putative transect lines from 2017-2019 and start points from 2017-2024). This will allow for assessment of the spatial relationship between different survey data sources towards future comparisons of community assemblages according to various sampled habitats.\n\nIMAGE ANALYSES\nDigital still images of 45 MP (8256 x 5504 pixels) from the FOBIS near-seafloor drift camera system were obtained over a series of transects, with a target interval collection of one image captured every 30-s. An altimeter attached to the camera system provided the height of the survey package off-bottom (one record approximately every second), and a pair of lasers spaced 10-cm apart allowed for the estimation of the field of view (FOV) in the digital still imagery. To reduce the number of still images to interpret for preliminary post-survey analysis of benthic organism occurrences, one image was selected approximately every 50 m along a transect using buffer tools in ArcGIS Pro v.2.8 (ESRI 2021). Still images were deemed unusable and removed from the dataset if there were insufficient light levels, too much turbidity, or if the altitude off-bottom exceeded 2.5 m. \nThe set of selected still images were randomized across all transects before being imported into the open-source image annotation software BIIGLE 2.0 (Langenkamper et al. 2017; Zuroweitz and Nattkenper 2021). Images were randomized to ensure rare organisms were captured and to account for a possible learning bias (i.e., discovering new/different organisms as annotation procedures progressed), as well as annotator fatigue. Image files were grouped in BIIGLE as projects by year with file volumes by transect. \nEach selected image was analyzed for presences of visible types (by taxon or morphotype), including mobile and sessile organisms on the seafloor using the method in BIIGLE where an image was zoomed in to the resolution of choice and ‘Lawnmower mode’ was activated (Zuroweitz and Nattkenper 2021). Once in Lawnmower mode, the bottom left image section becomes the first tile that is analyzed before forwarding to the next tile, ensuring no image area in a frame is missed or duplicated during the review. In each tile, annotations were applied to any type (taxon or morphotype) present using a rectangle to enclose the organism in view. For instances where an organism was larger than the tile being analyzed (e.g., a fish), annotations were not applied until all tiles were analyzed, and the image returned to full view. In some instances where an organism such as kelp or encrusting coralline algae occurred across the entire image, an annotation was applied via a point instead of a rectangle. Note that the annotations in BIIGLE ensured that a type, and its location in pixels were recorded by image. However, each separate occurrence of a type was not annotated; thus, the results are presences by image and not the sum of abundances or areas visible within an image.\nEach annotation corresponded to a designated label of a type, i.e. a species or higher defined-taxonomic level, or a morphotype. Identifications were limited by the environment (lighting, water turbidity), the image (resolution, depth of field, focus, and blurriness, i.e., the speed of the camera system over the seafloor), and by whether or not a type could be identified solely from image-based criteria. As such, identification labels were applied to the lowest taxonomic classification level possible with reasonable confidence and including input by taxonomic specialists. For morphotypes, labels were based on the visual assessment of morphological traits, for example ‘encrusting yellow dark sponge’. Considering no physical sediment samples were taken, occurrences are limited to organisms visible on the surface of the seafloor, leading to few reported burrowing (endobenthic) taxa. Uncertain identifications not at the species level were either labelled using higher classification levels (e.g., genus, family, order, class, phylum) or grouped as a specific morphotype (e.g., unidentified white rock crust). These morphotype group labels were necessary because of issues with either images or taxonomy. For images, identifications could be uncertain if not clear or with crab or Atlantic Cod. In other cases, the images may be insufficient to identify certain types, especially among sponges, bryozoans, and cnidarians. These require either microscopic examination or genetic analyses as several visually similar kinds (or unknown cryptic kinds) may be in view. Thus, these uncertain kinds were labelled by morphotypes or to general taxonomic levels, often with suggested taxa. Taxonomic names were obtained from the World Register of Marine Species (WoRMS 2025).\nThe collection of annotations were organized as a label tree in BIIGLE, functioning as a hierarchical set of groupings of taxa and morphotypes to apply to organisms in each image. For the St. Anns Bank surveys, the SAB2023 label tree was a fork (branch, or version) of the Benthic organism label tree for the Hudson 2018 Eastern Shore Islands CAMPOD imagery (Paulin et al. 2025). The SAB2024 label tree then forked from SAB2023 before simplifying groups of labels based on morphotypes and taxa observed. Species names and more general taxa labels (where species was unknown or could not be determined) were added to a label tree as they were encountered. Tentative taxa names were applied to labels using public and internal working image guides and resources based on visual resemblance and known distributions (i.e., Nozères et al. 2010; Command et al. 2024; Nozères et al. 2024; iNaturalist 2025; Paulin et al. 2025; WoRMS 2025; Goodwin pers. comm.). As of this report, the project label trees (titled SAB2023/2024) are not yet finalized as taxa under higher groupings, or unknown taxa may later be confirmed by taxonomic experts, including examples posted on the community site, iNaturalist.org. Presently, the annotations are for species, suggested or likely genus or species (indicated by an asterisk), broader classifications (class, order, etc.) and morphological trait groupings. Selected example images of organisms were uploaded to iNaturalist (https://www.inaturalist.org/projects/st-anns-bank-mpa-imagery-surveys) to aid in verifying species and genus identifications. Feedback from community members resulted in some suggested changes to identifications, which were then applied as BIIGLE annotations. \nNear-seafloor optical imagery survey data (both still imagery and continuous seafloor video) from both the 2023 and 2024 St. Anns Bank surveys are stored in an archive (duplicate versions of the imagery on two 50 TB desktop RAID devices) managed by P. Lawton, L.L. Teed, and the DFO Coastal Ecosystems Science Division data management team at the St. Andrews Biological Station, New Brunswick, Canada. As of October 2025, some FOBIS camera system imagery files have been loaded to open data portals; however the bulk of the imagery archive is still maintained on local RAID drives. Survey summary data and image locations are currently published on Canada’s open data portal (Lawton and Teed 2025), which will be updated when occurrence analysis is complete.","methodSteps":["IMAGE ANALYSES\nDigital still images of 45 MP (8256 x 5504 pixels) from the FOBIS near-seafloor drift camera system were obtained over a series of transects, with a target interval collection of one image captured every 30-s. An altimeter attached to the camera system provided the height of the survey package off-bottom (one record approximately every second), and a pair of lasers spaced 10-cm apart allowed for the estimation of the field of view (FOV) in the digital still imagery. To reduce the number of still images to interpret for preliminary post-survey analysis of benthic organism occurrences, one image was selected approximately every 50 m along a transect using buffer tools in ArcGIS Pro v.2.8 (ESRI 2021). Still images were deemed unusable and removed from the dataset if there were insufficient light levels, too much turbidity, or if the altitude off-bottom exceeded 2.5 m. \nThe set of selected still images were randomized across all transects before being imported into the open-source image annotation software BIIGLE 2.0 (Langenkamper et al. 2017; Zuroweitz and Nattkenper 2021). Images were randomized to ensure rare organisms were captured and to account for a possible learning bias (i.e., discovering new/different organisms as annotation procedures progressed), as well as annotator fatigue. Image files were grouped in BIIGLE as projects by year with file volumes by transect. \nEach selected image was analyzed for presences of visible types (by taxon or morphotype), including mobile and sessile organisms on the seafloor using the method in BIIGLE where an image was zoomed in to the resolution of choice and ‘Lawnmower mode’ was activated (Zuroweitz and Nattkenper 2021). Once in Lawnmower mode, the bottom left image section becomes the first tile that is analyzed before forwarding to the next tile, ensuring no image area in a frame is missed or duplicated during the review. In each tile, annotations were applied to any type (taxon or morphotype) present using a rectangle to enclose the organism in view. For instances where an organism was larger than the tile being analyzed (e.g., a fish), annotations were not applied until all tiles were analyzed, and the image returned to full view. In some instances where an organism such as kelp or encrusting coralline algae occurred across the entire image, an annotation was applied via a point instead of a rectangle. Note that the annotations in BIIGLE ensured that a type, and its location in pixels were recorded by image. However, each separate occurrence of a type was not annotated; thus, the results are presences by image and not the sum of abundances or areas visible within an image.\nEach annotation corresponded to a designated label of a type, i.e. a species or higher defined-taxonomic level, or a morphotype. Identifications were limited by the environment (lighting, water turbidity), the image (resolution, depth of field, focus, and blurriness, i.e., the speed of the camera system over the seafloor), and by whether or not a type could be identified solely from image-based criteria. As such, identification labels were applied to the lowest taxonomic classification level possible with reasonable confidence and including input by taxonomic specialists. For morphotypes, labels were based on the visual assessment of morphological traits, for example ‘encrusting yellow dark sponge’. Considering no physical sediment samples were taken, occurrences are limited to organisms visible on the surface of the seafloor, leading to few reported burrowing (endobenthic) taxa. Uncertain identifications not at the species level were either labelled using higher classification levels (e.g., genus, family, order, class, phylum) or grouped as a specific morphotype (e.g., unidentified white rock crust). These morphotype group labels were necessary because of issues with either images or taxonomy. For images, identifications could be uncertain if not clear or with crab or Atlantic Cod. In other cases, the images may be insufficient to identify certain types, especially among sponges, bryozoans, and cnidarians. These require either microscopic examination or genetic analyses as several visually similar kinds (or unknown cryptic kinds) may be in view. Thus, these uncertain kinds were labelled by morphotypes or to general taxonomic levels, often with suggested taxa. Taxonomic names were obtained from the World Register of Marine Species (WoRMS 2025).\nThe collection of annotations were organized as a label tree in BIIGLE, functioning as a hierarchical set of groupings of taxa and morphotypes to apply to organisms in each image. For the St. Anns Bank surveys, the SAB2023 label tree was a fork (branch, or version) of the Benthic organism label tree for the Hudson 2018 Eastern Shore Islands CAMPOD imagery (Paulin et al. 2025). The SAB2024 label tree then forked from SAB2023 before simplifying groups of labels based on morphotypes and taxa observed. Species names and more general taxa labels (where species was unknown or could not be determined) were added to a label tree as they were encountered. Tentative taxa names were applied to labels using public and internal working image guides and resources based on visual resemblance and known distributions (i.e., Nozères et al. 2010; Command et al. 2024; Nozères et al. 2024; iNaturalist 2025; Paulin et al. 2025; WoRMS 2025; Goodwin pers. comm.). As of this report, the project label trees (titled SAB2023/2024) are not yet finalized as taxa under higher groupings, or unknown taxa may later be confirmed by taxonomic experts, including examples posted on the community site, iNaturalist.org. Presently, the annotations are for species, suggested or likely genus or species (indicated by an asterisk), broader classifications (class, order, etc.) and morphological trait groupings. Selected example images of organisms were uploaded to iNaturalist (https://www.inaturalist.org/projects/st-anns-bank-mpa-imagery-surveys) to aid in verifying species and genus identifications. Feedback from community members resulted in some suggested changes to identifications, which were then applied as BIIGLE annotations. \nNear-seafloor optical imagery survey data (both still imagery and continuous seafloor video) from both the 2023 and 2024 St. Anns Bank surveys are stored in an archive (duplicate versions of the imagery on two 50 TB desktop RAID devices) managed by P. Lawton, L.L. Teed, and the DFO Coastal Ecosystems Science Division data management team at the St. Andrews Biological Station, New Brunswick, Canada. As of October 2025, some FOBIS camera system imagery files have been loaded to open data portals; however the bulk of the imagery archive is still maintained on local RAID drives. Survey summary data and image locations are currently published on Canada’s open data portal (Lawton and Teed 2025), which will be updated when occurrence analysis is complete."]},"countryCoverage":[],"collections":[],"dataDescriptions":[],"dataLanguage":"eng","purpose":"A total of 3381 still images of the seafloor were captured from 41 transects in a survey of the St. Anns Bank Marine Protected Area in August 2023 and 2024. A set of 639 images with a target of 50 m between images were reviewed for the presence of each type of visible taxa. Using the image annotation software BIIGLE, distinguishable organisms were identified to the lowest possible taxonomic level, with some given a morphotype label. Taxonomically, labels for arthropods, chordates, echinoderms, sponges, and other taxa across 14 phyla are provided. A total of 23392 annotations were applied by taxon and morphotype, with image examples for each type provided in an appendix. This report documents the context and use of taxon and morphotype annotations for reference in subsequent community assemblage analyses of occurrences in addition to the preparation for future annotations of abundances of important erect taxa such as crinoids.
","introduction":"A DFO Maritimes Region science project “Coastal seabed habitat inventory and biodiversity assessment in support of bioregional conservation network planning and development of Marine Protected Area monitoring programs”, funded under the DFO Science Marine Conservation Targets program from 2021 to 2025, has generated a renewed focus on using both SCUBA diving approaches and near-seafloor imaging tools to survey coastal and inner-shelf benthic habitats in support of the development of MPA ecological monitoring programs. In particular, this project supported the introduction (in 2022) of a new regional near-seafloor optical imaging system capable in its initial configuration of surveying to depths of 200 m. The camera system (hereafter referred to as the FOBIS system, for Fibre Optic-Based Imaging System) was co-developed by ocean technologists within DFO’s Ocean Engineering and Technology Section at the Bedford Institute of Oceanography, Dartmouth, Nova Scotia, and lead project scientist, Peter Lawton, at DFO’s Biological Station, Saint Andrews, New Brunswick.To document the presence of fauna and flora and examine possible temporal changes in benthic community assemblages, a two-year near-seafloor optical imagery survey was conducted with the FOBIS camera system, collecting continuous video coverage of the seafloor and periodic digital still images (additional survey details provided in Teed et al. in press). Near-seafloor imagery surveys involved a total of 41 drift-transects in the St. Anns Bank Marine Protected Area (MPA) off the coast of Cape Breton, Nova Scotia, Canada in August 2023 and 2024 (Figure 1). Background information and details pertaining to transect locations and broader survey objectives are outlined in the complementary initial mission report (Teed et al. in press), while details on the image annotation approach used to classify observed benthic fauna and flora are presented here. Specifically, we describe the use of the image annotation software BIIGLE (BioImaging Indexing, Graphical Labelling and Exploration – Langenkamper et al. 2017) to apply labels (listed in Appendix 1) to note organism presence and classify the organisms identifiable within a digital still camera image view. Examples of image annotations are also provided to give visual context to assist our team as the project progresses with conducting community composition analyses (Appendix 2).\tImage annotations are standardized labels applied to a feature of interest located in a specific area in an image (Nozères et al. 2024). Annotations, or labels, can also be applied to an entire image frame: for example, when recording dominant substrates or the presence of a single species of interest. The standardization arises from the application of a defined set of annotations, or label tree (often one or two label trees as the project progresses), in a BIIGLE project. The primary objective of 2023 and 2024 field surveys was to report on the occurrences of all visible taxa in selected images for development of biodiversity metrics and so provide a foundation to later potentially evaluate temporal and spatial changes in benthic habitat assemblages when compared to prior benthic imaging surveys (Lacharité et al. 2018; Lacharité and Brown 2019; Kenchington and Lirette 2023 – with the latter not yet analyzed/no annotations provided for these images currently). Additionally, visible taxa from the 2023 and 2024 imagery surveys could be compared to information on benthic invertebrates and demersal fish documented as by-catch species from the DFO (Department of Fisheries and Oceans Canada) Maritimes Summer Ecosystem Research Vessel Surveys (RV Surveys – Murillo et al. 2018, 2024; Mancion and Jeffery 2025). The present report documents the status of annotations of observed marine fauna and flora as of October 2025, and is neither a formal identification guide, nor an analytical report concerning benthic community attributes.
","gettingStarted":"Image annotation software: BIIGLE
Image field of view calculation software: ImageJ2
","acknowledgements":"We would like to acknowledge Kirk Phelan and Nelson Rice for engineering development of the near-seafloor optical imaging system, as well as Kirk Phelan, Torben Brydges and Pat Mowatt for field support in the 2023 and 2024 surveys. Thank you to the captains and crew of the CCGS M. Perley that provided the surface vessel platform and experienced seamanship to be able to operate the camera system in sometimes challenging sea conditions. Furthermore, we would like to thank Neo Paulin, Claude Nozères, Bárbara Neves and Claire Goodwin for their feedback on species identifications. This research was funded by the Department of Fisheries and Oceans Canada as part of the Marine Conservation Targets Program under the Maritimes Region project number 691.","pubDate":"2026-03-30T00:00:00.000+00:00","maintenanceUpdateFrequency":"AS_NEEDED","maintenanceDescription":"Will update if consensus on identifications to lowest taxonomic levels changes.","license":"http://creativecommons.org/publicdomain/zero/1.0/legalcode","dwca":{"coreType":"http://rs.tdwg.org/dwc/terms/Event","extensions":["http://rs.tdwg.org/dwc/terms/Occurrence","http://rs.tdwg.org/dwc/terms/MeasurementOrFact"],"modified":"2026-07-11T02:56:20.144+00:00"},"approximateCounts":{"occurrenceCount":15586}}