Contributors | Affiliation | Role |
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Gaylord, Brian | University of California - Davis: Bodega Marine Laboratory (UC Davis-BML) | Principal Investigator |
Ninokawa, Aaron Takeo | University of California - Davis: Bodega Marine Laboratory (UC Davis-BML) | Contact |
Heyl, Taylor | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
Rauch, Shannon | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
These data were generated by establishing a mussel bed in a laboratory flow tunnel. Each profile represents a period where chemistry (pH and O2) was measured at defined heights within and above the mussel bed. These profiles occurred at two places in the mussel bed. These data describe average conditions outside of the mussel bed during each profile. Freestream velocities and shear velocities were assumed constant during a profile.
Calcification and respiration rates were calculated as the fluxes of alkalinity and oxygen, respectively. Flux calculations were modified from McGillis et al, 2011 and Takeshita et al, 2016.
Methods described in detail in Ninokawa et al. (2020).
Known Issues: No oxygen data was collected for profiles 1-7. This also prohibits the calculation of alkalinity profiles, calcification rates, and respiration rates. Zero freestream velocities also prohibits the calculation of calcification and respiration rates due to the lack of sufficient turbulent mixing.
All data analyses were performed with R Statistical Software. The seacarb package was used for carbonate chemistry calculations and the marelac package was used for estimating oxygen flux out of the surface of the flow tunnel.
BCO-DMO Processing:
- Adjusted field/parameter names to comply with BCO-DMO naming conventions
- Missing data identifier ‘NA’ replaced with 'nd' (BCO-DMO's default missing data identifier)
- Added a conventional header with dataset name, PI names, version date
File |
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effects_of_mussels_on_seawater_chemistry_-_summary_data.csv (Comma Separated Values (.csv), 1.75 KB) MD5:96bf120f1a3f09064b53612789656455 Primary data file for dataset ID 869361 |
Parameter | Description | Units |
profile | profile identifier | unitless |
date | date when the profile was measured in format: YYYY-MM-DD | unitless |
freestream_velocity | freestream velocity held during the profile, calculated from a relationship with flow tunnel speed setting | m s-1 |
u_star | shear velocity during the profile, calculated from a relationship with flow tunnel speed setting | m s-1 |
bed_position | location of profile in the bed, 1=95 cm downstream of leading edge, 2=145 cm downstream of leading edge | unitless |
temperature | average top temperature during the profile | degrees celsius (°C) |
salinity | average top salinity during the profile | PSU |
top_ph | average top pH during the profile | unitless |
top_o2 | average top oxygen concentration during the profile | µmol kg-1 |
max_diff_ph | maximum observed difference in pH during the profile | unitless |
max_diff_o2 | maximum observed difference in oxygen concentration during the profile | µmol kg-1 |
calcification_rate | bed calcification rate calculated for the mussel bed as the areal flux of alkalinity during the profile | mmol hr-1 m-2 |
respiration_rate | bed respiration rate calculated for the mussel bed as the areal flux of oxygen during the profile | mmol hr-1 m-2 |
Dataset-specific Instrument Name | Nortek acoustic doppler profiler (ADP) |
Generic Instrument Name | Acoustic Doppler Current Profiler |
Dataset-specific Description | Nortek acoustic doppler profiler (ADP). Freestream velocity and u* were extracted from velocity profiles. A relationship between flow tunnel speed setting and freestream velocity and u* was used during period the ADP lacked sufficient particles in the water for accurate velocity measurements. |
Generic Instrument Description | The ADCP measures water currents with sound, using a principle of sound waves called the Doppler effect. A sound wave has a higher frequency, or pitch, when it moves to you than when it moves away. You hear the Doppler effect in action when a car speeds past with a characteristic building of sound that fades when the car passes. The ADCP works by transmitting "pings" of sound at a constant frequency into the water. (The pings are so highly pitched that humans and even dolphins can't hear them.) As the sound waves travel, they ricochet off particles suspended in the moving water, and reflect back to the instrument. Due to the Doppler effect, sound waves bounced back from a particle moving away from the profiler have a slightly lowered frequency when they return. Particles moving toward the instrument send back higher frequency waves. The difference in frequency between the waves the profiler sends out and the waves it receives is called the Doppler shift. The instrument uses this shift to calculate how fast the particle and the water around it are moving. Sound waves that hit particles far from the profiler take longer to come back than waves that strike close by. By measuring the time it takes for the waves to bounce back and the Doppler shift, the profiler can measure current speed at many different depths with each series of pings. (More from WHOI instruments listing). |
Dataset-specific Instrument Name | Presens Microx 4 with needle-type microsensor |
Generic Instrument Name | Oxygen Microelectrode Sensor |
Dataset-specific Description | O2 and temperature calibrate by the manufacturer. O2 calibration verified in seawater equilibrated with atmospheric O2 and sensors deviating from 100% were replaced. |
Generic Instrument Description | Any microelectrode sensor that measures oxygen. |
Dataset-specific Instrument Name | Honeywell Durafet III combination electrode |
Generic Instrument Name | pH Sensor |
Dataset-specific Description | Top pH sensor: Honeywell Durafet III combination electrode calibrated to total scale with spectrophotometric pH determination on discrete water samples
Profiling pH sensor: Honeywell Durafet III combination electrode calibrated to total scale by holding adjacent to the top pH sensor |
Generic Instrument Description | An instrument that measures the hydrogen ion activity in solutions.
The overall concentration of hydrogen ions is inversely related to its pH. The pH scale ranges from 0 to 14 and indicates whether acidic (more H+) or basic (less H+). |
Dataset-specific Instrument Name | Yellow Springs Instruments 6920 Multiparameter Sonde |
Generic Instrument Name | YSI Sonde 6-Series |
Dataset-specific Description | Top O2, salinity, and temperature sensor: Yellow Springs Instruments 6920 Multiparameter Sonde. O2 calibrated by holding adjacent to the profiling O2 sensor. Salinity calibrated with YSI 50 uS/cm Conductivity Standard. Temperature calibrated by manufacturer. |
Generic Instrument Description | YSI 6-Series water quality sondes and sensors are instruments for environmental monitoring and long-term deployments. YSI datasondes accept multiple water quality sensors (i.e., they are multiparameter sondes). Sondes can measure temperature, conductivity, dissolved oxygen, depth, turbidity, and other water quality parameters. The 6-Series includes several models. More from YSI. |
NSF Award Abstract:
The absorption of human-produced carbon dioxide into the world's oceans is altering the chemistry of seawater, including decreasing its pH. Such changes, collectively called "ocean acidification", are expected to influence numerous types of sea creatures. This project examines how shifts in ocean pH affect animal behavior and thus interactions among species. It uses a case study system that involves sea star predators, snail grazers that they eat, and seaweeds consumed by the latter. The rocky-shore habitats where these organisms live have a long history of attention, and new findings from this work will further extend an already-large body of marine ecological knowledge. The project provides support for graduate and undergraduate students, including underrepresented students from a nearby community college. The project underpins the development of a new educational module for local K-12 schools. Findings will moreover be communicated to the public through the use of short film documentaries, as well as through established relationships with policy, management, and industry groups, and contacts with the media.
Ocean acidification is a global-scale perturbation. Most research on the topic, however, has examined effects on single species operating in isolation, leaving interactions among species underexplored. This project confronts this knowledge gap by considering how ocean acidification may shift predator-prey relationships through altered behavior. It targets as a model system sea stars, their gastropod grazer prey, and macoalgae consumed by the latter, via four lines of inquiry. 1) The project examines the functional response of the focal taxa to altered seawater chemistry, using experiments that target up to 16 discrete levels of pH. This experimental design is essential for identifying nonlinearities and tipping points. 2) The project addresses both consumptive and non-consumptive components of direct and indirect species interactions. The capacity of ocean acidification to influence such links is poorly known, and better understanding of this issue is a recognized priority. 3) The project combines controlled laboratory experiments with field trials that exploit tide pools and their unique pH signatures as natural mesocosms. Field tests of ocean acidification effects are relatively rare and are sorely needed. 4) A final research phase expands upon the above three components to address effects of ocean acidification on multiple additional taxa that interact in rocky intertidal systems, to provide a broad database that may have utility for future experiments or modeling.
Funding Source | Award |
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NSF Division of Ocean Sciences (NSF OCE) |