Marine carbon dioxide removal (mCDR) approaches are under development to mitigate the effects of climate change by sequestering carbon in stable reservoirs, with potential co-benefits of local reduction of coastal acidification impacts. One such method is ocean alkalinity enhancement (OAE). A specific OAE method is the generation of aqueous alkalinity via electrochemistry to enhance the alkalinity of the receiving water by the extraction of acid from seawater, thereby avoiding issues of solid dissolution kinetics and the release of impurities into the ocean from alkaline minerals. While electrochemical acid extraction is a promising method for increasing the carbon dioxide sequestration potential of the ocean, the biological effects of increasing seawater alkalinity and pH within an OAE project site are relatively unknown. This study aims to address this knowledge gap by testing the effects of increased pH and alkalinity, delivered in the form of aqueous NaOH, on two eelgrass epifauna in the U.S. Pacific Northwest, Taylor’s sea hare (Phyllaplysia taylori) and eelgrass isopod (Idotea resecata), chosen for their ecological importance as salmon prey and for their roles in eelgrass ecosystems. Four-day experiments were conducted in closed bottles to allow measurements of the evolution of carbonate species throughout the experiment with water refreshed twice daily to maintain elevated pH, across pHNBS treatments ranging from 7.8 to 9.3. Sea hares experienced mortality in all pH treatments, ranging from 37% mortality at pHNBS 7.8 to 100% mortality at pHNBS 9.3. Isopods experienced lower mortality rates in all treatment groups, ranging from 13% at pHNBS 7.8 to 21% at pHNBS 9.3, which did not significantly increase with higher pH treatments. These experiments represent an extreme of constant exposure to elevated pH and alkalinity, which should be considered in the context of both the natural variation and the dilution of alkalinity experienced by marine communities across an OAE project site. Different invertebrate species will likely have different responses to increased pH and alkalinity, depending on their physiological vulnerabilities. Investigation of the potential vulnerabilities of local marine species will help inform the decision-making process regarding mCDR planning and permitting.

Eelgrass (Zostera marina) characteristics, sediment grain size distributions, sediment total organic carbon contents (TOC), carbon isotope ratios of sediment organic matter, and total carbon to total nitrogen ratios were measured at four lower intertidal sites in Bellingham Bay, Washington, July 2-5, 2019.

This dataset includes biological variables showing surf smelt spawning presence, geological variables describing beach composition, and sample locations using RTK-GPS. This field data was also used to run the Sea Level Affecting Marshes Model (SLAMM; Warren Pinnacle Consulting, Inc., Warren, Vt)) to predict the changes to beaches over time, and under different sea level rise scenarios. Field sampling took place on the northern part of Bainbridge Island, Puget Sound, Washington during summer and fall of 2010.

This data release presents eelgrass distributions and bathymetry data derived from acoustic surveys of Bellingham Bay, Washington. Survey operations were conducted between February 16 and February 21, 2019 (USGS Field Activity Number 2019-606-FA) by a team of scientists from the U.S. Geological Survey Pacific Coastal and Marine Science Center and Washington State Department of Ecology. Eelgrass and bathymetry data were collected from the R/V George Davidson equipped with a single-beam sonar system and global navigation satellite system (GNSS) receiver. The sonar system consisted of a Biosonics DT-X single-beam echosounder and 420 kHz transducer with a 6-degree beam angle. Depths from the echosounder were computed using sound velocity data measured using a YSI CastAway CTD during the survey. Positioning of the vessel was determined at 5 Hz using a Trimble R9s GNSS receiver and Trimble Zephyr Model 2 antenna operating in real time kinematic (RTK) mode. Differential corrections were transmitted by a cellular modem to the GNSS receiver on the survey vessel at 1-Hz from a GNSS continuously operating reference station operated by the Washington State Reference Network (WSRN; http://www.wsrn3.org/) located in the city of Bellingham (station BELI). Output from the GNSS and sonar systems were combined in real time by the Biosonics DT-X deck unit and output to a computer running HYPACK hydrographic survey software. Navigation information was displayed on a video monitor, allowing the vessel operator to navigate along predefined survey lines spaced at 25- to 100-m intervals alongshore at speeds of approximately 2 m/s. Acoustic backscatter data were analyzed using a custom graphical user interface (GUI) that implements a signal processing algorithm applied to each sonar sounding to extract the location of the bottom and presence of vegetation (Stevens and others, 2008 ). Individual acoustic returns along a survey line were grouped into packets of ten, and eelgrass percent cover was calculated as the fractional percent of acoustic returns that were classified as vegetated within each group, resulting in a estimate of percent cover every 4 to 5 m (depending on vessel speed). The positioning data from the bathymetric survey were postprocessed using Waypoint Grafnav to apply differential corrections with data recorded at the GNSS base station BELI and archived by the WSRN; these data superseded the original positions recorded in real time. The GUI was used to combine filtered sonar data with postprocessed positioning data and orthometric elevations relative to the NAVD88 vertical datum were computed using National Geodetic Survey Geoid12a offsets. The estimated vertical uncertainty of the bathymetric measurements ranged from 2.0 cm to 18.3 cm with a mean of 6.7 cm. Uncertainty in the vertical positions associated with pitch and roll of the survey vessel is unknown. The final point data are provided in a comma-separated text file and are projected in Cartesian coordinates using the Universal Transverse Mercator (UTM), Zone 10 north, meters coordinate system.

This dataset contains raw sampling data beginning in 1989 for a long-term environmental and seagrass monitoring station in Laguna Madre (“LM-151”). This project served to understand environmental drivers of long-term changes in seagrass condition within the Upper Laguna Madre, Texas. Environmental parameters measured within the water column include water depth, dissolved oxygen concentration, underwater light level, pH, salinity, Secchi depth (turbidity), water temperature, total suspended solids, and dissolved inorganic nitrogen and ammonium. Seagrass biological parameters measured are above/belowground biomass and shoot density. Typical seagrass species represented within the data include Halodule wrightii (shoal grass) and Syringodium filiforme (manatee grass). Sampling was dependent on funding/resource availability and local weather conditions, therefore temporal gaps in data may exist. Data are provided in CSV format.

Seafloor character, a combination of seafloor induration (surface hardness) and rugosity, was derived from multibeam echosounder (MBES) and annotated underwater video data collected offshore of the Eel River, California. The MBES and underwater video data were collected in support of the U.S. Geological Survey (USGS) California Seafloor Mapping Program, under a collaboration with the California State University Monterey Bay Seafloor Mapping Lab, the California Ocean Protection Council, and the National Oceanic and Atmospheric Administration (NOAA). Substrate observations from the underwater video were translated into Coastal and Marine Ecological Classification Standard (CMECS; Federal Geographic Data Committee, 2012) induration classes to use as training for a supervised numerical classification of the MBES data. The seafloor character raster is provided as a 2-meter resolution GeoTIFF.

Seafloor character, a combination of seafloor induration (surface hardness) and rugosity, was derived from multibeam echosounder (MBES) and annotated underwater video data collected offshore of the Eel River, California. The MBES and underwater video data were collected in support of the U.S. Geological Survey (USGS) California Seafloor Mapping Program, under a collaboration with the California State University Monterey Bay Seafloor Mapping Lab, the California Ocean Protection Council, and the National Oceanic and Atmospheric Administration (NOAA). Substrate observations from the underwater video were translated into Coastal and Marine Ecological Classification Standard (CMECS; Federal Geographic Data Committee, 2012) induration classes to use as training for a supervised numerical classification of the MBES data. The seafloor character raster is provided as a 2-meter resolution GeoTIFF.

This portion of the USGS data release presents eelgrass distributions derived from towed underwater video surveys of the Nisqually River delta, Washington in 2012 (USGS Field Activity Number D-01-12-PS). Eelgrass data were collected from the R/V George Davidson equipped with a towed underwater video system and global navigation satellite system (GNSS) receiver. The underwater video system consisted of a Splashcam standard definition video camera connected to a Sony GV-D1000 video monitor and tape recorder. Positioning of the survey vessel was determined at 1 Hz intervals using a Trimble R7 GNSS receiver and Trimble Zephyr Model 2 antenna. The positioning data from the GNSS were encoded onto the audio track of the digital video recording using Red Hen Systems (RHS) VMS200 hardware. Underwater video data were recorded as the vessel navigated along a series of shore-perpendicular transects at speeds between 1 and 2 knots. The underwater video recording was later reviewed and the presence or absence of eelgrass was determined for each 1-s segment of video tape. These data were used to evaluate the classification of single-beam sonar data acquired during the same time period.

This portion of the USGS data release presents eelgrass distributions derived from towed underwater video surveys of the Nisqually River delta, Washington in 2017 (USGS Field Activity Number 2017-614-FA). Eelgrass data were collected from the R/V George Davidson equipped with a towed underwater video system and global navigation satellite system (GNSS) receiver. The underwater video system consisted of a Splashcam standard definition video camera connected to a Sony GV-D1000 video monitor and tape recorder. Positioning of the survey vessel was determined at 1 Hz intervals using a Trimble R7 GNSS receiver and Trimble Zephyr Model 2 antenna. The positioning data from the GNSS were encoded onto the audio track of the digital video recording using Red Hen Systems (RHS) VMS200 hardware. Underwater video data were recorded as the vessel navigated along a series of shore-perpendicular transects at speeds between 1 and 2 knots. The underwater video recording was later reviewed and the presence or absence of eelgrass was determined for each 1-s segment of video tape. These data were used to evaluate the classification of single-beam sonar data acquired during the same time period.