Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
  • BCO-DMO Processing Description
  • Problem Description
• Parameters
• Instruments
• Project Information
• Funding

Sampling:
Daily trips were made to the sampling sites using small boats. Start and end dates of field missions:
March 28 - April 17, 2022
September 1 -& October 4, 2022
February 21 - April 13, 2023

Both apparently healthy and actively diseased colonies of Agaricia agaricites (14 diseased, 27 healthy), Acropora cervicornis (6 healthy), Colpophyllia natans (19 diseased, 20 healthy), Diploria labyrinthiformis (7 diseased, 19 healthy), Montastraea cavernosa (18 diseased, 20 healthy), Orbicella annularis (18 diseased, 24 healthy), Porites astreoides (8 diseased, 32 healthy) were sampled for various analyses. All work was completed by divers on SCUBA. Each sampled colony was marked for relocation by hammering a numbered cattle tag into the adjacent dead substrate and then photographed from above. Then, using either a hammer and chisel or underwater Nemo drill with a diamond tipped hole saw (no anvil), coral fragments approximately 4 x 4 centimeters (cm) were collected from each colony. Three fragments were collected from apparently healthy corals (HH), and six fragments from diseased corals, including three fragments immediately adjacent to the lesion boundary (DD) and three fragments from apparently healthy tissue (HD). All fragments were placed into individually labeled whirlpacks and transported to the surface. Sample scar edges on the sampled colonies were sealed with natural clay. Corals were rephotographed before and after sealing with the clay. Marked colonies were mapped using a camera time-paired to a GPS on a float that was towed above by the sampler. Once at the surface, one fragment from each sample type (HH, HD, DD) was processed for microbial analyses, gene expression, TEM, and histopathology (separate data sets).

Monitoring:
Using maps created using the GPS-paired images, divers on SCUBA relocated colonies, if possible. Colonies that were found were rephotographed, and the following was recorded: size estimates (length, width, and height), percent of the colony showing old mortality (defined as calyx degradation and algal recruitment), percent of the colony showing recent mortality (defined as bright white exposed skeleton with no algal recruitment), percent of living tissue that was bleached or paled, and disease identification (if applicable). Colony ID was confirmed by comparing monitoring photos to photos of the colony at sampling. All tissue was sampled from 15 of the 233 sampled colonies, and therefore these corals were not reassessed. At six months post-sampling, 159 corals were found, photographed, and monitored for health status. At one year post-sampling, 146 corals were found, photographed, and monitored for health status.

Instrument Details:
Corals were tagged with 2½ inch masonry nails and plastic cattle tags with unique IDs. Coral and sample-specific images were recorded with Olympus Tough TG-6 cameras in Olympus underwater housings. Either Milwaukee 3lb sledges and ¾ inch mason chisels or Nemo underwater drills with 1½ inch diamond hole saws (anvil removed) were used to collect fragments.

Each coral was assigned a representative health state at the monitoring period (either apparently healthy, diseased, or other health impairment) to fate track colonies and compare fates among the sampling health states.

- Imported original file "PREDICT_USVIShallowFateTracking_toupload.csv" into the BCO-DMO system.
- Marked "NA" as a missing data value (missing data are empty/blank in the final CSV file).
- Changed format of dates to YYYY-MM-DD.
- Renamed fields to comply with BCO-DMO naming conventions.
- Saved the final file as "986534_v1_usvi_fate_tracking.csv".

NSF Award Abstract:
Marine diseases have devastating impacts on ocean ecosystems and this work will directly examine the framework for understanding disease transmission in the ocean. A team of ecologists, ocean connectivity and disease modelers, microbiologists, and coral immunologists (from the University of Virgin Islands (UVI), Louisiana State University (LSU), Rice University, University of Texas-Arlington and the Woods Hole Oceanographic Institution) will develop a model that predicts transmission of a devastating Caribbean coral disease that has the potential to impact the economic value of coral reefs, including those located in the U.S. This project will support multidisciplinary field and laboratory research experiences of graduate students at multiple minority-serving institutions, and will provide undergraduate students with hands-on training in modeling, ecological and molecular analysis techniques. UVI and LSU are in EPSCoR jurisdictions and have diverse student bodies, including numerous under-represented minority (URM) students. The research team will collaboratively provide URM students with research experiences in STEM fields. Project findings will be broadly communicated through virtual public programming, and through the Virgin Islands Coral Disease Advisory Committee with updates on the vicoraldisease.org website. A coral disease response workshop for the U.S. Virgin Islands will also be held, in which project results will be presented and used to support disease response planning.

Over the last four decades, marine diseases have decimated ecosystem engineers in marine coastal ecosystems, including the rocky intertidal, seagrasses and coral reefs. The pathogens driving these diseases have frequently been challenging to isolate, characterize and confirm, in part because they affect multiple host species and can spread by ocean currents, as well as through individual contact. Here, we propose a multi-scale epidemic model for studying marine disease that addresses both within-host and within-patch disease dynamics, and explicitly acknowledges the dispersal of pathogens between populations. Our interdisciplinary research team of ecologists, connectivity and disease modelers, microbiologists, and coral immunologists will integrate the largest set of predictors of marine disease spread to date: individual host species traits that allow for disease resistance or susceptibility, local transmission within communities that may have unique community structure, and hydrodynamic connectivity among susceptible communities. Modeling will be supported with rich data sets of within- and among-patch population characteristics and disease dynamics as well as molecular data on species-level disease responses. This project will advance knowledge of infectious diseases by integrating multidimensional scales and differential host susceptibilities into existing epidemiological models. This model will particularly advance the framework for studying marine diseases and has the potential to elucidate the transmission properties of a devastating Caribbean coral disease (stony coral tissue loss disease) that fits the most confounding and notorious hallmarks of marine diseases: infection of multiple hosts by an elusive pathogen.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.