This dataset contains raw and annotated images from the CTD camera deployed during the TEMPO voyage.
Raw images were annotated by Maddie Brasier in Biigle as per the Antarctic Seafloor Annotated Imagery Database (AS-AID) (Gros et al. 2023, Jansen et al. 2023). Two annotation catalogues were used including the ‘CATAMI – mobile and indicator species’ in which labels were based on the CATAMI classification scheme (Althaus et al., 2015) and, ‘VME morpho-taxa’ based on the CCAMLR guide to VME indicator taxa (CCCAMLR, 2009).
Counts and percentage cover data of the identified species per image are given.
Metadata files required for Biigle uploads included.
Summary document of image processing included.
Most krill studies focus on the epipelagic zone (surface to ~250m), but recent observations indicate that they can also exist within the abyssal zone. As a part of the TEMPO voyage a deep sea camera mounted to the CTD rosette was used to observe krill at the ocean floor. As a result seafloor images were collected during every full depth CTD deployment during the voyage. In these analyses the images were used to identify benthic fauna, the taxa present will be compared to the corresponding eDNA samples collected during the same CTD deployment.
Taken from the summary document of image processing:
Images were collected during CTD deployments via a Canon HFG10 mounted on to frame of the rosette. The camera and lights were switched on 25 m above the seafloor during the CTD decent and captured a still image every 10 seconds. At this point the focus was set to infinity. The CTD was lowered to 3-5 m from the seabed, after 2 minutes the focus was adjusted to 1 m.
For each CTD deployment the highest quality image/s were selected for image analysis. Out of focus images were discarded, for some deployments multiple images were used as the if they captured different areas of the seabed and encompass as must potential benthic diversity as possible. Whilst the ship was as stationary as possible there was enough movement of the to capture different sections of the seabed with the roll of the ship and subsequent movement on the CTD cable. On average 2 images were used per station (Table 1). Whilst the best image/s were selected for each station in some instances there were no fauna present, or the image was out of focus (Table 1). During data analysis I suggest we remove the ‘unscorable’ out of focus images to prevent false negatives (i.e. a result that suggested no fauna present when actually no fauna scored because of out of focus image). Examples of high quality images and range images in Figure 1.
Images were annotated using the web-based software Biigle (Langenkämper et al. 2017) and were uploaded together with their metadata including date, time, latitude, longitude, water depth, height above seabed and image area.
Height above seabed was determined by the altimeter reading from the time each image was taken during the CTD deployment. The width and height of each image was calculated using a lens field calculator (https://www.deepsea.com/lens-field-calculator/), using the heigh above seabed and the sensor size of 1/3 inch and a native focal length of 4.25mm of the camera. From this the area calculated for each image and included in the metadata.
Images were annotated as per the Antarctic Seafloor Annotated Imagery Database (AS-AID) (Gros et al. 2023, Jansen et al. 2023). Two annotation catalogues were used including the ‘CATAMI – mobile and indicator species’ in which labels were based on the CATAMI classification scheme (Althaus et al., 2015) and, ‘VME morpho-taxa’ based on the CCAMLR guide to VME indicator taxa (CCCAMLR, 2009). A single scorer annotated all images (MB) any ambiguous fauna were reviewed by independent experts (Charley Gros (IMAS) and Melanie Mackenzie (Museum Victoria)) but in some cases were still unidentifiable. Some key taxa were not listed in either catalogue and were labelled as either ‘indicator species’ or ‘no id’ to be edited in post processing, these labels were also used for some ambiguous taxa and notes taken (Table 2).
