Dataset: Vegetative density data from two surveys of eelgrass flowering in shallow and deep zones at four different sites in Massachusetts, USA in 2019

ValidatedFinal no updates expectedDOI: 10.26008/1912/bco-dmo.847062.1Version 1 (2021-03-30)Dataset Type:Other Field Results

Principal Investigator: A. Randall Hughes (Northeastern University)

BCO-DMO Data Manager: Shannon Rauch (Woods Hole Oceanographic Institution)


Project: RUI: Collaborative Research: Trait differentiation and local adaptation to depth within meadows of the foundation seagrass Zostera marina (ZosMarLA)


Abstract

This dataset includes vegetative densities from two surveys of eelgrass flowering in shallow and deep zones at four different sites in Massachusetts, USA in 2019. The four sites were West Beach in Beverly (N 42.55921, W 70.80578), Curlew Beach in Nahant (N 42.42009, W 70.91553), Lynch Park in Beverly (N 42.54488, W 70.85842), and Niles Beach in Gloucester (N 42.59711, W 70.65592).

We conducted two surveys of four different eelgrass beds in Massachusetts during the summer of 2019. The four sites were West Beach in Beverly (N 42.55921, W 70.80578), Curlew Beach in Nahant (N 42.42009, W 70.91553), Lynch Park in Beverly (N 42.54488, W 70.85842), and Niles Beach in Gloucester (N 42.59711, W 70.65592). Surveys were done in both the shallow and deep zone. These zones were defined as being along the respective edges of the eelgrass beds. The exact depths of the zones varied from bed to bed. The first survey of each site was conducted at the end of June/early July. In these surveys, we counted the number of both vegetative and flowering shoots in 5-7 0.0625 m^2 quadrats from each of three previously established permanent quadrats per depth per site. This gave us a total of 15-21 0.0625 m^2 quadrats per depth per site. The second survey of each site was conducted in mid-August. Instead of doing the surveys from within the permanent quadrats, we did so outside of them to avoid overlap. We counted the number of vegetative and flowering shoots within 0.0625 m^2 quadrats every 2 m along a 30 m transect (that would be extended for each quadrat that had no eelgrass). This led to there being 15-18 quadrats per depth per site.

Related Datasets

IsRelatedTo

Dataset: Eelgrass shoot lengths
Relationship Description: These datasets all contain results from the same sampling effort (end of June/early July of 2019). Dataset "Permanent plot vegetative density" (847062) also contains additional results from an additional sampling effort in August of 2019.
Sotka, E., Hughes, A. R., Hanley, T. C., Hays, C. (2024) Eelgrass shoot lengths measured at two depths within each of four coastal sites in Massachusetts, USA in 2019. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2024-10-03 doi:10.26008/1912/bco-dmo.939440.1
IsRelatedTo

Dataset: Eelgrass shoot density and above-ground biomass
Relationship Description: These datasets all contain results from the same sampling effort (end of June/early July of 2019). Dataset "Permanent plot vegetative density" (847062) also contains additional results from an additional sampling effort in August of 2019.
Sotka, E., Hughes, A. R., Hanley, T. C., Hays, C. (2024) Quadrat-based measurements of eelgrass shoot density and above-ground biomass for plants growing in shallow and deep zones at four coastal sites in Massachusetts, USA in 2019. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2024-10-03 doi:10.26008/1912/bco-dmo.939467.1

Related Publications

Results

Von Staats, D. A., Hanley, T. C., Hays, C. G., Madden, S. R., Sotka, E. E., & Hughes, A. R. (2020). Intra-Meadow Variation in Seagrass Flowering Phenology Across Depths. Estuaries and Coasts, 44(2), 325–338. doi:10.1007/s12237-020-00814-0
Methods

Venables, W. N., & Ripley, B. D. (2002). Modern applied statistics with S (4th ed., Ser. Statistics and computing). Springer. URL: http://www.stats.ox.ac.uk/pub/MASS4
Software

R Core Team (2019). R: A language and environment for statistical computing. R v3.6.0. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/