Raw and filtered data on pigmentation patterns and scarring densities of Cuvier's beaked whales from three geographic regions Corresponding Author Name: Erin Falcone Institution: Marine Ecology and Telemetry Research Address: 2468 Camp McKenzie Tr NW Seabeck, WA 98380 USA Email: efalcone@marecotel.org Lead Author: Name: Frazer Guy Coomber Institution: The Mammal Society Address: The Mammal Society, Vlack Horse Cottage, 33 Milton Abbas, Blandford Forum, Dorest, DT110BL. UK Email: science@themammalsociety.org Date of data collection: 1998 to 2019 Geographic locations of data collected: Mediterranean - Roughly 43.949, 9.022 California - Roughly 33.449, - 119.013 Isla Guadalupe - Roughly 29.131, -118.245 Funding source information: File list: This repository contains 4 files relating to the pigmentation patterns and scarring density patterns collected using photographic idnetification techniques from wild Cuvier's beaked whales - Raw_pigmentation_variables_combined.csv - A csv stored data table with information on the pigmentation variables for the available animals measured. - Filtered_pigmentation_combined.csv - A csv stored data table with information on the pigmentation variables for the filtered animals, i.e. one sample per animal. - Raw_scarring_density_data_combined.csv - A csv stored data table with information on the scarring density variables for the available animals measured. - Filtered_scarring_density_combined.csv - A csv stored data table with information on the scarring density variables for the filtered animals, i.e. one sample per animal. File relationship: The raw and filtered datasets are related in the fact that one contains the raw available information and the filtered data contains only the information used in the analyses fort he corresponding data type (e.g., scarring density or pigmentation). There are currently no additional versions of this dataset Raw_pigmentation_variables_combined.csv # A csv-stored data table with information on the pigmentation variables for the available animals measured. # 218 rows # Please note that this dataset is of PICs (Photographic Identification Captures) and contains replicated samples (animals) # The csv contains the following fields: ## country - a four letter identifier to classify where the PIC was recorded from GUAD = animals collected from Guadalupe Island Mexico METR = animals collected from Californai, USA CIMA = animals collected from the Mediterranean Sea, Italy ## Animal_id - an identifying integer for each individual animal, note that identifiers relate to country so animal 1 from GUAD is not the same as animal 1 from METR ## Date - the date that the PIC was taken, the format is in dd/mm/yyyy ## Sex - the known sex of an individual based on the methods outlined in Coomber et al. 2016; Rosso et al. 2011 and Coomber et al. 2021 0 = an adult female animal 1 = an adult male animal ## ProVis - a quality score ranging 1 to 3 from best to worst, detailing the proportion of visible body above the waterline in the photograph ## Exposure - a quality score ranging 1 to 3 from best to worst, detailing the exposure quality of the photograph ## Sharpness - a quality score ranging 1 to 3 from best to worst, detailing the sharpness quality fo the photograph ## TotalROI - the number of ROIs visible for the photographic recapture ## FirstROI - the first visible ROI from the photographic capture ## LastROI - the last visible ROI from the photographic recapture ## Rostrum - boolean, was a photograph of the rostrum captured ## Blowhole - boolean, was a photograph of the blowhole captured ## Cape - boolean, was a photograph of the cape captured ## DF - boolean, was a photograph of the dorsal fin captured ## Diatoms - integer ranging from 0 - 7 indicating at the level of diatom coverage from the photographic recapture ## CCScar - integer, the number of cookie cutter shark scars ## Status - was the photographic capture measured for scarring based on the methods of Coomber et al., 2016 ## Dentition - categorical variable on the presence and status of erupted teeth ## Ovals - the presence and distinctivness of an animals ovals - see appendix Coomber et al., 2021 ## Crescents - the presence and distinctiveness of an animals crescents - see appendix Coomber et al., 2021 ## CrescentLength - the length of the crescents - see appendix Coomber et al., 2021 ## CapePattern - the cape pattern classifications - see appendix Coomber et al., 2021 ## CapeTexture - the cape texture classifications - see appendix Coomber et al., 2021 ## CapeExtent - the number of ROIs that the cape extends to - see appendix Coomber et al., 2021 ## CapeColor - the color classifications of the cape - see appendix Coomber et al., 2021 ## FlankColor - the color classifications of the flank - see appendix Coomber et al., 2021 ## Age - the age of the animal, 1 indicates an adult and 0 indicates a sub-adult Filtered_pigmentation_combined.csv # A csv-stored data table with information on the pigmentation variables for the filtered animals, i.e. one sample per animal. # 121 rows # The csv contains the following fields: ## recnum - unique identifier for the dataset ## country - a four letter identifier to classify where the PIC was recorded from GUAD = animals collected from Guadalupe Island Mexico METR = animals collected from Californai, USA CIMA = animals collected from the Mediterranean Sea, Italy ## animal - an identifying integer for each individual animal, note that identifiers relate to country so animal 1 from GUAD is not the same as animal 1 from METR ## sex - the known sex of an individual based on the methods outlined in Coomber et al. 2016; Rosso et al. 2011 and Coomber et al. 2021 0 = an adult female animal 1 = an adult male animal ## date - the date that the PIC was taken, the format is in dd/mm/yyyy ## ovals - the presence and distinctivness of an animals ovals - see appendix Coomber et al., 2021 ## cres - the presence and distinctiveness of an animals crescents - see appendix Coomber et al., 2021 ## cres_length - the length of the crescents - see appendix Coomber et al., 2021 ## cape_patt - the cape pattern classifications - see appendix Coomber et al., 2021 ## cape_text - the cape texture classifications - see appendix Coomber et al., 2021 ## cape_ext - the number of ROIs that the cape extends to - see appendix Coomber et al., 2021 ## cape_colour - the color classifications of the cape - see appendix Coomber et al., 2021 ## flank_colour - the color classifications of the flank - see appendix Coomber et al., 2021 ## animalID - a unique identifier used to identify an animal to country and id Raw_scarring_density_data_combined.csv # A csv-stored data table with information on the scarring density variables for the available animals measured. # 827 rows # Each row represents an individual ROI # The csv contains the following fields: ## country - a four letter identifier to classify where the PIC was recorded from GUAD = animals collected from Guadalupe Island Mexico METR = animals collected from Californai, USA CIMA = animals collected from the Mediterranean Sea, Italy ## ROI - The Region Of Interest, the identifier for the morphometric position the information on scarring relates to ROI1 = head ROI9 = directly below the dorsal fin See Fig 2A Coomber et al., 2021 ## ID - an identifying integer for each individual animal, note that identifiers relate to country so animal 1 from GUAD is not the same as animal 1 from METR ## Side - The side of the animal that the photographic capture was taken on r = Right l = Left ## Sex - the known sex of an individual based on the methods outlined in Coomber et al. 2016; Rosso et al. 2011 and Coomber et al. 2021 0 = an adult female animal 1 = an adult male animal ## age - the age of the animal, 1 indicates an adult and 0 indicates a sub-adult ## Ratio - the scarring density measured as the proportion of scarred to total pixels within a ROI ## id - serial integer for identifing each row of the data ## Date - the date that the PIC was taken, the format is in dd/mm/yyyy Filtered_scarring_density_combined.csv # A csv-stored data table with information on the scarring density variables for the filtered animals, i.e. one sample per animal. # Each row represents an individual animal # The csv contains the following fields: ## country - a four letter identifier to classify where the PIC was recorded from GUAD = animals collected from Guadalupe Island Mexico METR = animals collected from Californai, USA CIMA = animals collected from the Mediterranean Sea, Italy ## animal - an identifying integer for each individual animal, note that identifiers relate to country so animal 1 from GUAD is not the same as animal 1 from METR ## side - The side of the animal that the photographic capture was taken on r = Right l = Left ## sex - the known sex of an individual based on the methods outlined in Coomber et al. 2016; Rosso et al. 2011 and Coomber et al. 2021 0 = an adult female animal 1 = an adult male animal ## date - the date that the PIC was taken, the format is in dd/mm/yyyy ## dorsal_coverage - a photographaph capture quality score used to filter data, all values are 3 - indicating that in this filtered dataset all captures have the essential data from ROI 7 through 9 ## roi789 - the scarring density measured as the proportion of scarred to total pixels within ROIs 7,8 and 9 ## provis - a quality score ranging 1 to 3 from best to worst, detailing the proportion of visible body above the waterline in the photograph ## exposure - a quality score ranging 1 to 3 from best to worst, detailing the exposure quality of the photograph ## sharpness - a quality score ranging 1 to 3 from best to worst, detailing the sharpness quality fo the photograph ## qual_score - the combined quality scores above used to filter the data