Point Sampling Data for Eelgrass (Zostera marina) and Widgeongrass (Ruppia marina) Abundance in Embayments of the North Pacific Coast of Baja California, Mexico

Point Count Sampling: Boat-based sampling were conducted in Bahia San Quintin (BSQ), Laguna Ojo de Liebre (LOL), and Laguna San Ignacio (LSI) over a 9 to 19-day period in late fall and early winter of 1998, 1999, 2005, and 2012. A point sampling approach was used in 1998, 1999, and 2005, following a systematic random design, where points were distributed evenly across each of the embayments (BSQ: 500 m spacing between points; LOL and LSI: 1 km spacing between points) and accessed by boat using a global positioning system (GPS) unit. The survey area was restricted to points located within high intertidal zone (+1.5 m mean lower low water, MLLW; upper limit of widgeongrass) to the shallow subtidal (–2.5 m MLLW; deepest depth reachable by snorkeling). This survey area encompassed the majority of the spatial extent of eelgrass (75–80 percent in LOL/LSI and greater than 90 percent in BSQ). In 2012 surveys were restricted to only BSQ and previously identified eelgrass areas within this bay because of time and logistical constraints. Thus, there was only one site estimate (BSQ) for eelgrass abundance in 2012. Sampled points were surveyed by snorkeling in dry suits primarily during high tide. At each point, we measured water depth with a tape measure attached to a pole, estimated percent cover of eelgrass, widgeongrass and all macro-seaweed species combined and common seaweed genus (Ulva, Codium, Gracilaria) or divisions (Phaeophyta [Brown seaweeds]; Rhodophyta [Red seaweeds]) within four, 0.25-m sq quadrats, and assessed water clarity as a measurement of water depth when a 20 cm-diameter Secchi disk disappeared from view when lowered from the surface of the water. If eelgrass or widgeongrass was present at a point, five representative plants were collected from each quadrat and measured for shoot length. Water depth (m) measurements were standardized to MLLW by subtracting the measured water depth from the closest publicly available tidal gauges with consideration to observed offsets in the timing of tidal curves. A rapid, visual estimation technique was used to assess abundance of seagrasses and seaweeds. This method is quick yet robust and highly repeatable, thereby minimizing among-observer differences in estimates of percent cover of seagrasses and seaweeds. The cover of seagrasses and seaweeds present in a quadrat was assigned a Braun-Blanquet (BB) visual cover score between 0.0 and 5.0 (Braun-Blanquet 1972).

Calibration Sampling: To establish the relationship between the abundance index and aboveground biomass for each seagrass species, eelgrass and widgeongrass were harvested annually within 12–37 calibration quadrats (0.25-m sq) in each embayment. Percent cover (BB score) was assessed and seagrass shoots (aboveground parts only) within each quadrat were removed, cleaned, and 10 representative shoots were measured for shoot length. Samples were then dried to constant mass and weighed to determine biomass per quadrat, which was scaled to grams per square meter.

Fixed Site Sampling: Eelgrass aboveground biomass (g m-2) and shoot length (m, meristem to longest leaf) collections were taken during low tide in three general periods: fall migration (1 Nov to 15 Dec), winter (16 Dec to 15 Feb) and spring migration (15 Feb to 31 Mar) during 1997-2006 and 2011-2013. Eelgrass was sampled at fixed sites (1997–2006 and 2011-2013) and along 50 m-long transects (2011–2013) placed in the mid to high (-0.2 to 0.5 m mean lower low water (mllw)) and low (-0.7 to -0.3 m mllw) intertidal of major eelgrass beds. At each site or along each transect 4-5, 0.1 m-2 or 0.25 m-2 quadrats were randomly placed and all eelgrass shoots within each quadrat clipped. Samples were cleaned, and all dead material, rhizomes and flowering shoots were removed. Ten representative shoots were measured for length and all shoots dried to constant mass and weighed to determine aboveground biomass. The estimates for each quadrat were then scaled to gm-2 and averaged across all samples to calculate an annual biomass estimate.