Dataset: Eelgrass shoot metrics from ecological field surveys in six regions along the eastern Pacific coast in June through August of 2019, 2020, and 2021.

Field transect surveys

Field surveys of eelgrass meadow sites were conducted at mid-summer low tides at field sites along the west coast of North America in the U.S. and Canada.  Samples and data were collected within the intertidal area of 32 eelgrass meadows distributed in six regions (Alaska, British Columbia, Washington, Oregon, California -Bodega Bay, and California -San Diego). Surveys were conducted between late June and early August in 2019, 2020, and 2021 by teams from six institutions.

For each site, three 20 meter transects were laid parallel to the shore at the shoreward (upper edge) of continuous eelgrass, and three lower (intertidal) 20 meter transects were laid at least 4 meters closer to the water.  Along each transect, individual eelgrass shoots (blades/leaves) were collected for analysis at 4, 8, 12, 16, and 20 meters).  Leaf and shoot samples were transported in individual containers on ice to the laboratory for immediate processing. 

Transect locations were recorded using a hand-held GPS (exact model varied between field locations). Salinity was measured at the time of sampling using a refractometer. Temperature loggers (HOBO MX 2201 and UA-001-64, Onset, Bourne, MA) were deployed at each eelgrass meadow site to provide a continuous record of in situ temperature.  For HOBO data, see https://www.bco-dmo.org/dataset/877355 and Related Datasets section below.

Laboratory (Morphology and Imaging)

In the lab, eelgrass blades were cleaned and prepared for morphology and imaging to capture disease metrics (see https://www.bco-dmo.org/dataset/879780). Shoot morphology measurements (sheath length, number of leaves, canopy height) were taken by hand in the laboratory.  The third-rank leaf from each shoot was analyzed for epiphyte load and grazing scars.  Epiphytes were gently scraped from the third-rank leaf onto a pre-weighed foil tin using a flexible plastic ruler.  Tins were dried at 60 degrees Celsius until the mass was constant.  Epiphyte mass was calculated using the values for the dry weight of the tin with and without the epiphyte sample.  The balances used to measure the epiphyte mass had precision of 0.001 grams. Epiphyte load was standardized as the mass of epiphytes per unit of leaf area. 

Third-rank leaves were further analyzed for disease metrics through imaging.  Cleaned leaves were placed between sheets of acetate and imaged at high resolution (600 dpi) using an Epson Perfection V550 scanner. The high-resolution images were saved in TIFF format and then processed using a program developed by the authors. The Eelgrass Lesion Image Segmentation Application (EeLISA) uses machine learning to identify healthy and diseased eelgrass tissue and outputs the following metrics:

• disease prevalence (presence or absence of disease on a given leaf)
• disease lesion area (absolute size of wasting disease lesions), and
• disease severity (proportion of leaf area damaged by disease).

~ For details on the development, testing, and training of EeLISA, see Rappazzo et al. (2021).
~ For methodology details, see Aoki et al. (2022)
~ Additional details for the field surveys are available in the Eelgrass Disease Project Handbook.
~ For 16S rRNA amplicon sequencing of eelgrass associated bacteria, refer to NCBI BioProject PRJNA802566 in the Related Datasets section below.