This study uses large eddy simulations to investigate nutrient transport and uptake in suspended macroalgal farms. Various farm configurations and oceanic forcing conditions are examined, with the farm base located near the nutricline depth. We introduce the Damkohler number Da to quantify the balance between nutrient consumption by macroalgae uptake and supply by farm-enhanced nutrient transport. Most cases exhibit Da<1, indicating that farm-generated turbulence sufficiently contributes to upward nutrient fluxes, supporting macroalgae growth. High Da and starvation may occur in fully grown farm blocks, a configuration that generates weakest turbulence, particularly when combined with densely planted macroalgae or under weak flow conditions. Flow stagnation within the farm due to macroalgae drag may constrain the uptake efficiency and further increase the starvation risk. Mitigation strategies involve timely harvesting, avoiding dense macroalgae canopies, and selecting farm locations with robust ocean currents and waves. This study provides insights for sustainable macroalgal farm planning.

While yearly budgets of CO2 and evapotranspiration (ET) above forests can be readily obtained from eddy-covariance measurements, the quantification of their respective soil (respiration and evaporation) and canopy (photosynthesis and transpiration) components remains an elusive yet critical research objective. To this end, methods capable of reliably partitioning the measured ET and F_c fluxes into their respective soil and plant sources and sinks are highly valuable. In this work, we investigate four partitioning methods (two new, and two existing) that are based on analysis of conventional high frequency eddy-covariance (EC) data. The physical validity of the assumptions of all four methods, as well as their performance under different scenarios, are tested with the aid of large eddy simulations, which are used to replicate eddy-covariance field experiments. Our results indicate that canopies with large, exposed soil patches increase the mixing and correlation of scalars; this negatively impacts the performance of the partitioning methods, all of which require some degree of uncorrelatedness between CO2 and water vapor. In addition, best performance for all partitioning methods were found when all four flux components are non-negligible, and measurements are collected close to the canopy top. Methods relying on the water-use efficiency (W) perform better when W is known a priori, but are shown to be very sensitive to uncertainties in this input variable especially when canopy fluxes dominate. We conclude by showing how the correlation coefficient between CO2 and water vapor can be used to infer the reliability of different W parameterizations.

It is well known that the motion of flexible vegetation leads to drag reduction in comparison to rigid vegetation. In this study, we use a numerical model to investigate how the detailed motion of kelp fronds in response to forcing by surface gravity waves can impact the drag exerted by the kelp on waves. We find that this motion can be characterized in terms of three dimensionless numbers: (1) the ratio of hydrodynamic drag to buoyancy, (2) the ratio of blade length to wave excursion, and (3) the Keulegan-Carpenter number, which measures the ratio of drag to inertial forces. We quantify drag reduction, and find that inertial forces can significantly impact the amplitude of kelp motion and amount of kelp drag reduction. Under certain wave conditions, inertial forces can cause kelp fronds to accelerate more quickly relative to the wave, which can lead to increased drag reduction and reduced wave energy dissipation. In some conditions, frond motion leads to drag augmentation in comparison to rigid fronds. Additionally, we discuss other features of kelp motion, such as the degree of asymmetry, and their relationship with enhanced drag reduction.

A document by Marcelo Chamecki. Click on the document to view its contents.