Seagrass beds are important coastal habitats, providing critical habitat for a wide-range of associated taxa, stabilizing shorelines, and acting as biogeochemical hotspots. Due to their location in shallow coastal systems, seagrasses are exposed to myriad anthropogenic threats leading to seagrass loss at a global scale. Two threats that seagrasses face are mechanical damage (e.g., propellor scarring) and overgrazing during population booms of herbivores. Here we surveyed seagrass systems in St. Andrew Bay and St. Joseph Bay, Florida to quantify seagrasses, propellor scars, and urchins throughout the system along the same 50m transect. St. Andrew bay was divided into 3 segments: North Bay, West Bay, St. Andrew Bay. Between May 4th and July 12th, 2023 we surveyed 95 randomly selected sites, 26 in St. Andrew Bay, 26 in North Bay, 19 in West Bay, and 24 in St. Joseph Bay. Sixteen sites were revisited to assess repeatability of sampling protocols. This data file includes surveys of seagrass canopy height, seagrass and macroalgae percent cover, and seagrass shoot density. Related data files for these surveys include urchin (Lytechinus variegatus) counts and size data, and propellor scar prevalence and size data. Water quality data may also be added at a later date. See the Related Datasets section for more information on currently available data.

Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
  • BCO-DMO Curation Notes
• Data Files
• Supplemental Files
• Related Datasets
• Parameters
• Instruments
• Project Information
• Funding

Survey Location

Survey sites were randomly selected from points generated in ArcGIS by overlaying a 300 x 300 m grid on the continuous seagrass shapefile obtained from Florida Department of Environmental Protection. Initially 30 sites per bay segment were randomly selected from the intersection of the grid. Due to safety concerns and logistical constraints some sites were not surveyed.

Seagrass and macroalgae percent cover

At each site seagrass and macroalgae were surveyed within a haphazardly placed 2m x 2m plot. Four 0.25m x 0.25m quadrats divided into 25 equally sized grid cells were haphazardly placed within the 2m x 2m quadrat. Within each smaller quadrat seagrass and macroalgae percent cover was assessed by counting the number of grid cells the taxa occupied.

Seagrass canopy height

Seagrass canopy height was measured four times within each smaller quadrat by holding a ruler perpendicularly to the sediment. Seagrass shoot density for each species present was counted within a 0.10m x 0.10m quadrat placed within each 0.25m x 0.25m quadrat.

Data was recorded on paper datasheets in the field and manually entered. A different person reviewed the data entry. Seagrass shoots were counted within 0.10 x 0.10 m quadrats in the field. These counts were converted to shoots per square meter by dividing the count by the quadrat area, or 0.01 m2. To assess percent cover in the field, researchers counted the number of 5 cm × 5 cm grid cells within a 0.25 × 0.25 m quadrat occupied by the taxon. To obtain a percent cover this count was then divided by 25 (the total number of grid cells) and multiplied by 100. 

 

This section documents curation actions performed prior to publication review with the submitter, and additional information relevant to understanding and reusing this dataset. It distinguishes changes made to the submitted (meta)data from unresolved issues and/or enhancements that improve future reuse and interoperability.

CURATION ACTIONS PERFORMED ON DATA

- Loaded survey_canopyheight.csv with header row 1; missing values set to "", "nd", "NA"
- Loaded survey_macroalgae_percentcover.csv with header row 1; missing values set to "", "nd"
- Loaded survey_seagrass_percentcover_shootdensity_updated.csv, with "" "nd" "NA" set as missing values
- Loaded survey_seagrass_percentcover_shootdensity.csv with header row 1; missing values set to "", "nd", "NA"
- Joined survey_seagrass_updated into survey_seagrass on row-number key ({#}) using inner mode, pulling in the quadrat column; source resource deleted after join
- Reordered survey_seagrass columns to uID, date_time_UTC, date_time_local, local_timezone, siteID, latitude, longitude, general_location, quadrat, Taxa, Percent.cover, Shoot.density
- Renamed survey_macroalgae columns Taxa to taxa_macroalgae and Percent.cover to percent_cover_macroalgae to enable concatenation
- Renamed survey_seagrass columns Taxa to taxa_seagrass, Percent.cover to percent_cover_seagrass, and Shoot.density to shoot_density_seagrass to enable concatenation
- Concatenated survey_canopyheight, survey_macroalgae, and survey_seagrass tables into new table survey_combined, mapping canopy1-canopy4 to canopy_1_seagrass_ht through canopy_4_seagrass_ht and unioning remaining columns; added source_file column recording originating table name; treated "", "nd", and "NA" as missing values so union-introduced blanks and sentinel values became nulls for later type casting
- Converted date_time_UTC from "M/D/YYYY H:MM" format to ISO 8601 UTC datetime string output
- Created date_time_CDT column as string copy of date_time_local only where local_timezone equals "America/Chicago", null otherwise
- Created date_time_EDT column as string copy of date_time_local only where local_timezone equals "America/New_York", null otherwise
- Converted date_time_CDT string values to ISO 8601 datetime type using "M/D/YYYY H:MM" format, skipping null rows
- Converted date_time_EDT string values to ISO 8601 datetime type using "M/D/YYYY H:MM" format, skipping null rows
- Deleted date_time_local and local_timezone columns
- Reordered columns to: uID, date_time_UTC, date_time_CDT, date_time_EDT, siteID, latitude, longitude, general_location, quadrat, taxa_macroalgae, taxa_seagrass, canopy_1_seagrass_ht through canopy_4_seagrass_ht, percent_cover_macroalgae, percent_cover_seagrass, shoot_density_seagrass, source_file
- Replaced periods with spaces in taxa_macroalgae values for readability
- Replaced periods with spaces in taxa_seagrass values for readability
- Replaced exact matches of "271" in siteID with "271.0" to match the uID site ID, as requested by submitter
- Output as 1006527_v1_seagrass_macroalgae_coverage_canopy.csv

CURATION ACTIONS PERFORMED ON METADATA

- BCO-DMO's standard metadata entry and text formatting steps were performed.

ISSUES POTENTIALLY IMPACTING REUSE

- N/A

Coverage: Florida Panhandle

NSF Award Abstract:
This project seeks to determine how ecological memory, shaped by an extreme disturbance, informs the response of coastal ecosystems to multiple stressors at population, community, and ecosystem levels. Seagrass ecosystems are among the most highly productive ecosystems on earth, yet are vulnerable to disturbance by both human activity and natural processes. Hurricane Dorian was a Category 5 hurricane that hit the Bahamas in 2019. By comparing seagrass communities in the direct path of the storm with neighboring areas that were less impacted, this project is evaluating how ecological memory might affect responses of seagrass ecosystems to common human-caused and natural stressors. The investigators are early-career scientists, and results from this study are likely to inform conservation, management, and restoration of seagrass ecosystems. They are providing substantial educational opportunities for students in the United States and in the Bahamas, including virtual and hands-on field research experiences for undergraduate students, some from groups traditionally underrepresented in science. Facilitated by Friends of the Environment, a local NGO on Abaco Island, virtual reality videos and curricula will also enhance STEM educational opportunities for Bahamian high school students

Seagrass ecosystems, a widespread and ecologically important nearshore system, may be shaped by the ecological memory of past disturbances. These legacies may influence how seagrass ecosystems respond to environmental change. The investigators will conduct new research that complements seven years of existing data in a study system in the path of Hurricane Dorian in the Bahamas to assess how ecological memory shapes the response of coastal seagrass beds at multiple levels of biological organization. They are using a combination of modeling, field observations, field experiments, and laboratory analyses to compare highly and minimally hurricane-impacted sites to determine: the distribution and relative abundance of three seagrass species; the relative abundance and species diversity of naturally occurring invertebrate and vertebrate grazers; overall species richness, functional diversity, and habitat complexity of each field site; seagrass growth rates and primary productivity; and abiotic environmental characteristics — irradiance, temperature, and nutrient content— of ambient seawater. They will sample twenty plots per site each quarter—including unaltered controls and experimental plots simulating mechanical damage, increased grazing pressure, and both mechanical damage and grazing. The goal is to provide a better understanding of how ecological memory drives the outcome of current ecological processes, which in turn will inform conservation and restoration efforts as seagrasses continue to decline globally.

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.

​This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).