Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
  • BCO-DMO Processing Description
  • Problem Description
• Related Publications
• Related Datasets
• Parameters
• Instruments
• Project Information
• Funding

This data is from a flume experiment undertaken at Friday Harbor Laboratories in July 2023 as part of a project investigating how the metabolic activity of marine organisms can alter the water chemistry of their interstitial spaces, and how these microscale alterations affect interactions in coastal ecosystems. 

This dataset presents velocity and turbulence data measured using a Nortek Vectrino. 

Additional data on bulk seawater chemistry from HOBO loggers and interstitial water chemistry from Pyroscience microsensors can be viewed at https://www.bco-dmo.org/dataset/982681 (see also Related Datasets section below).

A flume experiment was conducted at Friday Harbor Laboratories where flow and chemical gradients were measured within and above a dense aggregation of mussels (Mytilus trossolus). Four experimental flume speeds were examined: Q=quarter inch per second, H=half inch per second, O=one inch per second, and OH=one and a half inches per second. Data collection occurred over five days (July 24-28th, 2023) with a complete set of profiles measured at each background speed (n=4) every day. This led to a total of 20 profiles taken at 5 mussel bed locations, including 5 replicates of chemistry profiles and 3 replicates of velocity profiles at each of the background speeds: 0.25, 0.5, 1, 1.5 inch/sec or 0.6, 1.3, 2.5, 3.8 cm/sec respectively. A background velocity in inches was initially used because this was how the flume’s motor was set up.

Velocity profiles were taken over an experimental mussel aggregation in a recirculating seawater flume at Friday Harbor Laboratories (Friday Harbor, WA) using a Nortek Vectrino. Acoustic Doppler devices use sound waves and measure velocity fluctuations underwater using the Doppler effect. The Vectrino measures velocity in three dimensions (x,y,z) and has a duplicate sensor measuring the vertical z direction twice (z1 and z2). This is important as the vertical velocity component of turbulent flows is a key contributor to the mixing processes that occur, along with the exchange of energy, nutrients and particulates. The measurement volume has a height of 0.4 cm and diameter of 0.6 cm and is located 5 cm below the Vectrino’s transducer. A sampling frequency of 25 Hz was used with a nominal velocity range of +/- 0.3. Velocity measurements were taken for at least 3 minutes and were visually inspected for large fluctuations that may have been due to insufficient particles in the flume. Due to this, and the issue that the Vectrino needs the particles that mussel beds filter out, the flume was seeded with a mixture of water and fine clay to improve stability and accuracy of measurements if needed. Measurements were taken at a minimum of 11 different heights at a certain location in the aggregation. Setup included attaching the Vectrino to a metal stand using a ring clamp. The stand was marked every 0.5 cm for easy and consistent instrument movement during profiling. To measure interstitial gradients, a small hole was created in the mussel aggregation by removing a couple of mussels so that measurements could be taken in the bottom of the bed without interference from the mussels themselves. While this isn’t ideal, the hole was made as small as possible, and O’Donnell (2008) suggests that holes within the bed smaller than 5cm do not significantly impact flow.  

Raw data from the Vectrino is uploaded to Matlab and a function called vectrino_mussel.m is used to compute statistics such as mean/fluctuating velocities and Reynolds stresses over 10-minute averages. Reynolds stress is defined as u-prime, w-prime (u'w') bar or the average of the product between the instantaneous horizontal (u') and vertical (w') velocity fluctuations.

???Something more needed here... ??? Something about how the Frequencies, mean velocities, and spectrum values... a best fit -5/3 slope line is fit to the data and a corresponding dissipation measurement is outputted using the formula: 
                            S(k)=9/55*(4-cos^2(theta))/3*1.56*diss^(2/3)*f^(-5/3)*(u/2*pi)^(2/3)

(See Supplemental Files section for Matlab script)

- Imported data from source files: VP_Q_.txt, VP_H_.txt, VP_H_.txt, VP_OH_.txt, VP2_Q_.txt, VP2_H_.txt, VP2_H_.txt, VP2_OH_.txt, VP3_Q_.txt, VP3_H_.txt, VP3_H_.txt, VP3_OH_.txt
- Concatenated text files into a single CSV file
- Added new columns for Trial, Day, Date, Flume speed (descriptors and values)
- Rounded values to 3 decimal places (5 for smaller numbers)

NSF Award Abstract:
The project investigates how the metabolic activity of dense aggregations of marine organisms alter the water chemistry of their interstitial spaces, and how these microscale alterations feedback to affect the organisms’ interactions in coastal ecosystems. The research team focuses on bivalve mussels, foundation species that form dense ‘beds’ typically known for facilitating other species by ameliorating harsh flow conditions. This ability can become a liability, however, if flow is not sufficient to flush the interstitial spaces and steep, metabolically-driven concentration gradients develop. The research evaluates whether corrosive chemical microclimates (such as low oxygen or low pH) are most extreme in low flow, high temperature conditions, especially for dense aggregations of mussels with large biomass and/or high respiration rates, and if they negatively impact mussel beds and the diverse biological communities they support. The research addresses a global societal concern, the impact of anthropogenic climate change on coastal marine ecosystems, and has potential applications to aquaculture and biofouling industries by informing adaptation strategies to “future-proof” mussel farms in the face of climate change and improved antifouling practices for ships, moorings, and industrial cooling systems. The project forges new collaborations with investigators from three campuses and integrates research and education through interdisciplinary training of a diverse group of graduate, undergraduate and high school students. STEM education and environmental stewardship is promoted by the development of a K-12 level science curriculum module and a hand’s-on public exhibit of bivalve biology at a local shellfish farm. Research findings are disseminated in a variety of forums, including peer-reviewed scientific publications and research presentations at regional, national and international meetings.

The research team develops a framework that links environmental conditions measured at a coarse scale (100m-100km; e.g., most environmental observatories) and ecological processes at the organismal scale (1 cm – 10 m). Specifically, the project investigates how aggregations of foundation species impact flow through interstitial spaces, and how this ultimately impacts water chemistry immediately adjacent to the organisms. The research focuses on mytilid mussels, with the expectation that the aggregation alters the flow and chemical transport in two ways, one by creating a physical resistance, which reduces the exchange, and the other by enhancing the exchange due to their incurrent/excurrent pumping. These metabolically-driven feedbacks are expected to be strongest in densely packed, high biomass aggregations and under certain ambient environmental conditions, namely low flow and elevated temperature, and can lead to a range of negative ecological impacts that could not be predicted directly from coarse scale measures of ambient seawater chemistry or temperature. The team develops computational fluid dynamic (CFD) models to predict interstitial flows and concentration gradients of dissolved oxygen and pH within mussel beds. The CFD model incorporates mussel behavior and physiological activity (filtration, gaping, respiration) based on published values as well as new empirical work. Model predictions are compared to flow and concentration gradients measured in mussel aggregations in the laboratory and field. Finally, the team conducts several short-term experiments to quantify some of the potential negative ecological impacts of corrosive interstitial water chemistry on mussel aggregations, such as reduced growth, increased dislodgement, increased predation risk, and reduced biodiversity. Because the model is based on fluid dynamic principles and functional traits, the framework is readily adaptable to other species that form dense assemblages, thereby providing a useful tool for predicting the ability of foundation species to persist and provide desirable ecosystem services under current and future multidimensional climate scenarios.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.