Thalassia testudinum seagrass weights from biomass cores collected across the Western Atlantic from March to May 2023

Website: https://www.bco-dmo.org/dataset/917690
Data Type: Other Field Results, experimental
Version: 1
Version Date: 2023-12-28

Project
» Collaborative Research: The tropicalization of Western Atlantic seagrass beds (Tropicalization Seagrass Beds)
ContributorsAffiliationRole
Campbell, JustinSmithsonian Institution (NMNH)Principal Investigator, Contact
Newman, SawyerWoods Hole Oceanographic Institution (WHOI BCO-DMO)BCO-DMO Data Manager

Abstract
This dataset includes seagrass (Thalassia testudinum) aboveground and belowground weights from 15cm biomass cores collected in Spring 2019 across the Western Atlantic. Bocas del Toro, Panama; Bonaire; Little Cayman, Cayman Islands; Carrie Bow, Belize; Puerto Morelos, Mexico; Andros, Bahamas; Eleuthera, Bahamas; Corpus Christi, Texas; Galveston, Texas; Naples, Florida; Crystal River, Florida; St. Joes, Florida; and Bermuda.


Coverage

Location: Subtropical Western Atlantic
Spatial Extent: N:32.263611111111 E:-64.830555555556 S:9.351388888889 W:-97.034722222222
Temporal Extent: 2019-03-01 - 2019-05-23

Methods & Sampling

50 small seagrass (all comprised of one species, Thalassia testudinum) plots (0.25m2) were established at 13 shallow sites in the Western Atlantic. Each plot was assigned to one of ten treatments comprising a factorial manipulation of caging, nutrient supply, and canopy clipping: (1) control (2) partial cage (3) full cage (4) added nutrients (5) added nutrients + partial cage (6) added nutrients + full cage (7) full cage + half canopy clip (8) full cage + full canopy clip (9) full cage + added nutrients + half canopy clip (10) full cage + added nutrients + full canopy clip. After the experiment (approx. 1 year) 15cm diameter biomass cores were taken in each plot. To do this, the core was carefully placed over the seagrass and lowered to the sediment surface. The core was then inserted into the sediment (approx 10cm) using a twisting motion to sever belowground rhizomes. The core was then carefully removed and all captured above and belowground vegetative biomass was placed into a mesh bag and gently rinsed underwater. In the lab, the aboveground green leaf material was separated from the belowground material using a razor blade. Leaf material was also scraped clean of any epiphyte loading. Above and belowground material was dried separately in aluminum tares in a 60C oven. Any additional macroalgae found inside the core was also separately dried.


BCO-DMO Curation Notes

Curation Actions Performed on Data
- Loaded biom_weight_data.xlsx and treated blank cells, "nd", and "NA" as missing values.
- Converted latitude and longitude from degrees–minutes–seconds to decimal degrees. Latitude was recorded as north and longitude as west.
- Converted date_collected from %m-%d-%y to the date format %Y-%m-%d.
- Removed units from dry-weight column names, such as changing greenleaf_drywt (g) to greenleaf_drywt.
- Set the appropriate data type for each column, including text, dates, numbers, and integers.
- Added descriptions, standard-name IDs, and units to the column metadata.
- Marked latitude and longitude as the primary location parameters.
- Saved the processed data file as 917690_v1_TEN_seagrass_biomass_weights.csv.

Curation Actions Performed on Metadata
- Standard FAIR metadata curation principles have been applied to the metadata associated with this dataset where possible.

Known Issues [Potentially Impacting Reuse]
- Data file and metadata as presented have not been validated by the dataset author.
- Supporting citations for papers associated with the methods used for the generation of this data have not been provided.
- Three "Halodule" text values exist in the otherwise numeric otherveg1_drywt column of the primary data file; their intended meaning and proper placement or treatment have not been confirmed by the submitter, which may affect interpretation and reuse of these data.


Problem Description

No issues related to this dataset have been disclosed by the dataset author.

[ table of contents | back to top ]

Data Files

File
917690_v1_TEN_seagrass_biomass_weights.csv
(Comma Separated Values (.csv), 120.30 KB)
MD5:f04e288ab9e47f42b07605275be2369b
Primary data file for dataset ID 917690, version 1

[ table of contents | back to top ]

Related Publications

Fourqurean, J. W., Campbell, J. E., Rhoades, O. K., Munson, C. J., Krause, J. R., Altieri, A. H., Douglass, J. G., Heck, K. L., Paul, V. J., Armitage, A. R., Barry, S. C., Bethel, E., Christ, L., Christianen, M. J. A., Dodillet, G., Dutton, K., Frazer, T. K., Gaffey, B. M., Glazner, R., … Wilson, S. S. (2023). Seagrass Abundance Predicts Surficial Soil Organic Carbon Stocks Across the Range of Thalassia testudinum in the Western North Atlantic. Estuaries and Coasts, 46(5), 1280–1301. https://doi.org/10.1007/s12237-023-01210-0
Results

[ table of contents | back to top ]

Parameters

ParameterDescriptionUnits
site

Site name / location

unitless
latitude

Latitude in decimal degrees

decimal degrees
longitude

Longitude in decimal degrees

decimal degrees
recorder

recorder

unitless
season

summer (Apr-Oct) ; winter (Oct-Apr)

unitless
date_collected

mm/dd/yyyy

unitless
plot

plot number (1-50)

unitless
clipping

level of clipping; no=no clipping; partial=half canopy removed; full=full canopy removed

unitless
nutrients

level of nutrients; ambient=no added nutrients; enriched=added nutrients

unitless
cage

level of cage; no=no cage; partial=partial 4-sided cage; full=full cage

unitless
greenleaf_drywt

above ground green leaf biomass

grams (g)
sheath_drywt

below ground sheath biomass

grams (g)
root_drywt

below ground root biomass

grams (g)
rhizome_drywt

below ground rhizome biomass

grams (g)
root_rhizome_drywt

belowground rhizome + root biomass

grams (g)
otherveg_identification

additional macroalgae taxa

unitless
otherveg1_spp

additional macroalgae taxa

unitless
otherveg1_drywt

additional macroalgae dry wt

grams (g)
otherveg2_spp

additional macroalgae taxa

unitless
otherveg2_drywt

additional macroalgae dry wt

grams (g)
otherveg3_spp

additional macroalgae taxa

unitless
otherveg3_drywt

additional macroalgae dry wt

grams (g)
otherveg4_spp

additional macroalgae taxa

unitless
otherveg4_drywt

additional macroalgae dry wt

grams (g)
otherveg5_spp

additional macroalgae taxa

unitless
otherveg5_drywt

additional macroalgae dry wt

grams (g)


[ table of contents | back to top ]

Instruments

Dataset-specific Instrument Name
Custom made stainless steel push corer
Generic Instrument Name
Push Corer
Dataset-specific Description
A custom made stainless steel push corer (15cm diameter) was used to collect the seagrass biomass samples.
Generic Instrument Description
Capable of being performed in numerous environments, push coring is just as it sounds. Push coring is simply pushing the core barrel (often an aluminum or polycarbonate tube) into the sediment by hand. A push core is useful in that it causes very little disturbance to the more delicate upper layers of a sub-aqueous sediment. Description obtained from: http://web.whoi.edu/coastal-group/about/how-we-work/field-methods/coring/

Dataset-specific Instrument Name
Analytical balance
Generic Instrument Name
scale or balance
Dataset-specific Description
All samples were weighed on an analytical balance (resolution - 0.001 g).
Generic Instrument Description
Devices that determine the mass or weight of a sample.


[ table of contents | back to top ]

Project Information

Collaborative Research: The tropicalization of Western Atlantic seagrass beds (Tropicalization Seagrass Beds)


Coverage: Western Atlantic


NSF Award Abstract:
The warming of temperate marine communities is becoming a global phenomenon, producing new biotic interactions that can result in a series of cascading effects on ecosystem structure. For example, the poleward expansion of herbivore populations can lead to the consumption of habitat-forming vegetation, which alters the ecological services provided by coastal environments (a phenomenon known as tropicalization). Many of the habitats at risk, such as kelp forest and seagrass beds, provide foundational habitat that supports complex food webs. Seagrass meadows along the Gulf of Mexico are currently experiencing an influx of tropical grazers, however a integrated understanding of how these communities might ultimately respond is lacking. This project describes the first experiment to quantify the disruptive effect of tropicalization on the ecology of a widely-distributed seagrass. A major contribution of this project will be the development of a seagrass research collaborative network to serve as a platform for broader scientific inquiry and future collaboration. The collaboration spans a total of 11 institutions, and this network will foster extensive collaborations among junior and senior scientists, as well as many undergraduate and graduate students. Given the geographic scope of this work, the research team will further pursue outreach opportunities across the network by hosting a series of public lectures and science café events promoting topics in marine ecology and conservation.

This study will develop a large-scale manipulative experiment across the Caribbean, premised upon a comparative network of 15 marine sites, which will quantify how temperature and light interact with grazer effects on the dominant tropical seagrass, Thalassia testudinum. Sites have been selected along a latitudinal gradient (from Bermuda to Panama), such that light and temperature vary, allowing the investigators to test for the effects of abiotic factors on the ecological effects of increased grazing (tropicalization simulated via artificial leaf clipping). At each of the 15 marine sites, grazing treatments will be crossed with nutrient manipulations in a factorial design for 18 weeks, after which seagrass structure and functioning will be assessed via measurements of areal productivity, shoot density, aboveground biomass, and carbohydrate storage. Experiments will be conducted both in the summer and winter seasons, when abiotic gradients are at their weakest and strongest, respectively. Emerging statistical techniques in hierarchical mixed modeling and structural equation modeling will further allow for integration of experimental and observational data.



[ table of contents | back to top ]

Funding

Funding SourceAward
NSF Division of Ocean Sciences (NSF OCE)

[ table of contents | back to top ]