Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • BCO-DMO Curation Notes
  • Problem Description
• Related Publications
• Parameters
• Project Information
• Funding

Updates are planned for this dataset to extend the time range into 2027 as part of this project.

Day trips aboard a small fieldwork boat in Harrington Sound, Bermuda, from the Bermuda Aquarium Museum and Zoo dock, during October, 2022.

We dived on multiple locations in Harrington Sound and Flatts inlet using teams of 2 or 3 divers. Following Ajemian et al. (2012), divers excavated quadrats (0.5 x 0.5 m or 0.75 x 0.75 m) that were placed at three random distances along a 25 m long transect tape. Sediments were excavated by hand to a depth of approximately 15 cm, with all live hard shelled invertebrates placed into 8 mm mesh bags.  Samples were sorted, measured, and identified at the surface. 

Curation Actions Performed on Data

Version 1:
- zero-padded time notations for standardization purposes (9:21 -> 09:21)
- removed seconds (:00) from time notation for standardization purposes after discussion with submitter
- added ISO_DateTime_UTC values for in and out times for standardization purposes

Main file 964199_v1_benthic.csv processing workflow:
- Loaded Excavations.csv with headers row 1, all columns cast to strings, missing values "" treated as null, named 964199_v1_benthic
- Converted Date column from format %d/%m/%Y to datetime output format %Y-%m-%d
- Applied find/replace to Time_In_ADT and Time_Out_ADT columns to standardize single-digit hour notation (e.g. 9:21 to 09:21) to match consistent format, per data manager instruction
- Applied find/replace to remove trailing seconds (:00) from Time_In_ADT and Time_Out_ADT columns after discussion with submitter
- Converted Time_In_ADT from string to time type using format %H:%M, timezone Atlantic/Bermuda
- Converted Time_Out_ADT from string to time type using format %H:%M, timezone Atlantic/Bermuda
- Computed new datetime column ISO_DateTime_UTC_In by combining Date and Time_In_ADT, converting from Atlantic/Bermuda timezone to UTC, output format %Y-%m-%dT%H:%MZ
- Computed new datetime column ISO_DateTime_UTC_Out by combining Date and Time_Out_ADT, converting from Atlantic/Bermuda timezone to UTC, output format %Y-%m-%dT%H:%MZ
- Set column types and formats: Aperture_mm (number), Common_Name (string), Date (date, %Y-%m-%d), Depth_ft (integer), Depth_mm (number), Dist_Along_Transect_m (integer), Excavation_ID (string), Height_mm (number), ISO_DateTime_UTC_Out (datetime), ISO_DateTime_UTC_In (datetime), Latitude (number), Length_mm (number), Longitude (number), Siphon_Channel_Aperture_mm (number), Site_Name (string), Species_Name (string), Time_In_ADT (time), Time_Out_ADT (time)
- Saved as final table: 964199_v1_benthic.csv

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Version 2:
- Additional data were provided to BCO-DMO to extend the range of this dataset in the submitted file BDA_Benthic_Sampling.csv which differs from the v1 submitted file Excavations.csv in the following ways:
- Time range of data extended from 2022 (v1) -> 2022-2024 (v2).
- Scope expanded: 8 sites → 28 sites
- Excavation_ID standardized: inconsistent ES##/E## format → consistent zero-padded ES0## format
- Time fields not included in v2: Time_In_ADT/Time_Out_ADT (see notes below about potential issues for data reuse)
- Siphon channel measurement not included in v2: Siphon_Channel_Aperture_mm
- Area & Heading fields added (not in v1)

Main file 964199_v2_benthic.csv processing workflow:

- Loaded BDA_Benthic_Sampling.csv as table 964199_v2_benthic, treating empty string as missing value
- Corrected longitude values so all are negative (appropriate for this geographic area) by prepending a minus sign to any positive longitude value
- Converted Date column from %m-%d-%Y format to %Y-%m-%d date format
- Updated column metadata (descriptions, standard names, units) for Aperture_mm, Area_m2, Common_Name, Date, Depth_ft, Dist_Along_Transect_m, Excavation_ID, Heading, Height_mm, Lattitude, Length_mm, Longitude, Site_Name, Species_Name, Width_mm
- Set column types: Aperture_mm, Area_m2, Height_mm, Lattitude, Length_mm, Longitude, Width_mm as number; Depth_ft, Dist_Along_Transect_m, Heading as integer; Date as date; Common_Name, Excavation_ID, Site_Name, Species_Name as string
- Standardized duplicate Site_Name variants to "Gibbet's Island" and "Flatt's Inlet" to match apostrophe styling used in the previous dataset version
- Fixed duplicated text in Common_Name value "Black date Black date mussel" to "Black date mussel"
- Made common name entries consistently one label for each organism: Common_Name values "topshell" to "Topshell" and "atlantic pearl oyster" to "Atlantic Pearl Oyster"
- Renamed column Lattitude to Latitude to correct spelling
- Saved as final table: 964199_v2_benthic.csv

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Curation Actions Performed on Metadata
- Standard metadata entry and formatting of provided metadata.

Version 1:
- Species Name Verification: Species names were checked against the World Register of Marine Species (WoRMS) during quality review. All names matched a WoRMS name exactly (as of 2025-03-25).
Version 2:
- Species Name Verification: Names checked on 2026-09-08 for the newly provided v2 data. All names matched a WoRMS name exactly.
- Supplemental file benthic_species_list.csv added which is the unique list of organism names (scientific and common) along with their taxonomic identifiers.

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Known Issues [Potentially Impacting Reuse]
- Time columns were dropped in the version 2 of this dataset. Thus ISO datetime with timezone field was not added to the table as had been done in the first version.
- Duplicate rows in the data table are assumed to be different individuals of the same dimensions that occurred at the same position in the transect. Interpretation of duplicate rows were not specifically mentioned in the dataset metadata but this assumption was made due to the nature of the data collection and subject matter.
- Non-standard unit: Depth_ft reports depth in feet rather than meters, the standard unit for oceanographic data.

NSF Award Abstract:
Shellfish (mollusks, crustaceans, etc.) are facing unprecedented pressures under global climate change, which is threatening the variety of ecosystem services these animals provide to coastal communities. While much research has been dedicated to understanding how changing ocean conditions can influence shellfish development, far less has explored the potential impacts from increasing populations of large, shell-crushing predators (i.e., rays, turtles, etc.) that are experiencing poleward expansions of their ranges. This knowledge gap is likely due to the challenges of working with these mobile species, which require novel technology to track their dynamic distribution and thus foraging effects on shellfish communities. This project will build fundamental knowledge on marine habitats susceptible to predation from large mobile predators in order to ensure a sustainable future for shellfish species. Further, the work will provide guidance to costly shellfish restoration programs that are otherwise “flying blind” with respect to predation risk. The project will have local, regional, and global educational dimensions. Firstly, this project will strengthen FAU’s graduate programs by supporting a graduate student and providing a platform for the PI to develop a new graduate course, which will be offered and evaluated twice throughout the award period. Additionally, numerous undergraduate summer interns and middle-high school students will be recruited to interact with the PI via immersive, hands-on field excursions. Lastly, the fascination of the general public and students with these charismatic animals and the project’s tangible technological components will facilitate developing an interactive “Audio Waves” exhibit at a local outreach center, which will be evaluated several times during the project and slated for permanent display.

Our scientific understanding of the ecological role of large mobile durophages (i.e., shell-crushing predators) is limited due to challenges presented by the elusive nature of these species. These shortcomings hinder our scientific understanding of their role in benthic community dynamics. Filling such knowledge gaps requires novel approaches that can detect and classify predator-prey interactions in situ. Using multiple large predator models (rays, sea turtles, fish, and crabs), the project will: 1) capture and characterize predator feeding (shell-crushing) sounds and shell fragmentation patterns, 2) understand in situ detection constraints of the predation signal within the context of natural underwater noise using simulations, and 3) quantify the distribution of predator foraging impacts across two model seascapes in Bermuda and Florida via integration of habitat- and individual-based (animal tags) passive acoustics. Detection and classification (by both predator and prey) will be completed using novel application of machine-learning techniques, which will be used to automate predation event extraction from extensive data archives. Recording equipment will be strategically distributed across seascapes to permit a multi-scale understanding of durophagy and testing of theoretical models of predation (e.g., optimal/central place foraging). Long-term monitoring will also provide an opportunity to assess the role of environmental/oceanographic variables in driving these interactions. Consequently, this work will fill a large knowledge gap in the dynamics of marine food webs.