| Contributors | Affiliation | Role |
|---|---|---|
| Nickols, Kerry J. | California State University Northridge (CSUN) | Principal Investigator, Project Coordinator |
| Dunbar, Robert B. | Stanford University | Co-Principal Investigator |
| Hirsh, Heidi | Stanford University | Scientist, Contact |
| Monismith, Stephen G. | Stanford University | Scientist |
| Mucciarone, David | Stanford University | Scientist |
| Takeshita, Yuichiro | Monterey Bay Aquarium Research Institute (MBARI) | Scientist |
| Traiger, Sarah | United States Geological Survey (USGS) | Scientist |
| Soenen, Karen | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
These data are published in Hirsh et al., see related publications section.
Two ADCPs were deployed consecutively <10 m from the kelp mooring site (Macrocystis pyrifera, 36° 37.297’ N, 121° 54.102’ W), both measuring at 0.5 m vertical resolution:
Current directions were corrected for declination: true north was 13.12° degrees from magnetic north.
Velocity measurements from the two ADCP deployments were rotated into cross-shore and alongshore velocity components using the principal axes calculated (princax function in Matlab) for each deployment. The principle axes for the two kelp deployments were within 2° of each other. Individual current profiles were smoothed using a cubic smoothing spline (Matlab csaps package; smoothing parameter = 0.8).
The top 10% of the water column and velocity > 0.3 m/s was replaced with NaN.
BCO-DMO Processing Notes:
| File |
|---|
adcp_kelp_concat.csv (Comma Separated Values (.csv), 108.24 MB) MD5:8f14c834a3eae4974f3ddd776ce947d6 Primary data file for dataset ID 826431 |
| Parameter | Description | Units |
| Mooring_ID | Mooring name: kelp = inside kelp forest mooring | unitless |
| Deployment_ID | Deployment 1 or 2 at mooring | unitless |
| ISO_DateTime_UTC | Timestamp (date and time) in ISO format, UTC (yyyy-mm-ddThh:mmZ) | unitless |
| Zbin_Depth | Depth, meters above bottom | meters (m) |
| Velocity | Velocity | meters per second (m/s) |
| Velocity_Component | Velocity components: cross-shore and alongshore | unitless |
| Latitude | Latitude of mooring location, south is negative | decimal degrees |
| Longitude | Longitude of mooring location, west is negative | decimal degrees |
| Dataset-specific Instrument Name | Nortek Signature and RDI Teledyne-RDI workhorse ADCPs |
| Generic Instrument Name | Acoustic Doppler Current Profiler |
| Dataset-specific Description | Two ADCPs were deployed consecutively at the kelp mooring site, both measuring at 0.5 m vertical resolution:
Deployment 1: Nortek Signature 1000, June 12 to August 7, 2018
Deployment 2: RDI 1200 kHz Workhorse Sentinel, August 7 to October 4, 2018 |
| 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). |
| Website | |
| Platform | Mooring - Hopkins Marine Station |
| Start Date | 2018-06-08 |
| End Date | 2018-10-04 |
| Description | This deployment represents the mooring itself and data that has been acquired at this site or in close proximity of it, and are considered samples "inside a kelp forest":
ADCP data: |
NSF Award Abstract:
Kelp forest ecosystems are of ecological and economic importance globally and provide habitat for a diversity of fish, invertebrates, and other algal species. In addition, they may also modify the chemistry of surrounding waters. Uptake of carbon dioxide (CO2) by giant kelp, Macrocystis pyrifera, may play a role in ameliorating the effects of increasing ocean acidity on nearshore marine communities driven by rising atmospheric CO2. Predicting the capacity for kelp forests to alter seawater chemistry requires understanding of the oceanographic and biological mechanisms that drive variability in seawater chemistry. The project will identify specific conditions that could lead to decreases in seawater CO2 by studying 4 sites within the southern Monterey Bay in Central California. An interdisciplinary team will examine variations in ocean chemistry in the context of the oceanographic and ecological characteristics of kelp forest habitats. This project will support an early career researcher, as well as train and support a postdoctoral researcher, PhD student, thesis master's student, and up to six undergraduate students. The PIs will actively recruit students from underrepresented groups to participate in this project through Stanford University's Summer Research in Geosciences and Engineering (SURGE) program and the Society for Advancement of Hispanics/Chicanos and Native Americans in Science (SACNAS). In addition, the PIs and students will actively engage with the management community (Monterey Bay National Marine Sanctuary and California Department of Fish and Wildlife) to advance products based on project data that will assist the development of management strategies for kelp forest habitats in a changing ocean.
This project builds upon an extensive preliminary data set and will link kelp forest community attributes and hydrodynamic properties to kelp forest biogeochemistry (including the carbon system and dissolved oxygen) to understand mechanistically how giant kelp modifies surrounding waters and affects water chemistry using unique high-resolution measurement capabilities that have provided important insights in coral reef biogeochemistry. The project sites are characterized by different oceanographic settings and kelp forest characteristics that will allow examination of relationships between kelp forest inhabitants and water column chemistry. Continuous measurements of water column velocity, temperature, dissolved oxygen, pH, and photosynthetically active radiation will be augmented by twice-weekly measurements of dissolved inorganic carbon, total alkalinity, and nutrients as well as periods of high frequency sampling of all carbonate system parameters. Quantifying vertical gradients in carbonate system chemistry within kelp forests will lead to understanding of its dependence on seawater residence time and water column stratification. Additional biological sampling of kelp, benthic communities, and phytoplankton will be used to 1) determine contributions of understory algae and calcifying species to bottom water chemistry, 2) determine contributions of kelp canopy growth and phytoplankton to surface water chemistry, and 3) quantify the spatial extent of surface chemistry alteration by kelp forests. The physical, biological, and chemical data collected across multiple forests will allow development of a statistical model for predictions of kelp forest carbonate system chemistry alteration in different locations and under future climate scenarios. Threshold values of oceanographic conditions and kelp forest characteristics that lead to alteration of water column chemistry will be identified for use by managers in mitigation strategies such as targeted protection or restoration.
| Funding Source | Award |
|---|---|
| NSF Division of Ocean Sciences (NSF OCE) | |
| NSF Division of Ocean Sciences (NSF OCE) |