Net-zero greenhouse gas (GHG) emissions targets are driving interest in opportunities for biomass-based negative emissions and bioenergy, including from marine sources such as seaweed. Yet the biophysical and economic limits to farming seaweed at scales relevant to the global carbon budget have not been assessed in detail. We use coupled seaweed growth and technoeconomic models to estimate the costs of global seaweed production and related climate benefits, systematically testing the relative importance of model parameters. Under our most optimistic assumptions, sinking farmed seaweed to the deep sea to sequester a gigaton of CO2 per year costs as little as US$480 per tCO2 on average, while using farmed seaweed for products that avoid a gigaton of CO2-equivalent GHG emissions annually could return a profit of $50 per tCO2-eq. However, these costs depend on low farming costs, high seaweed yields, and assumptions that almost all carbon in seaweed is removed from the atmosphere (that is, competition between phytoplankton and seaweed is negligible) and that seaweed products can displace products with substantial embodied non-CO2 GHG emissions. Moreover, the gigaton-scale climate benefits we model would require farming very large areas (>90,000 km2)—a >30-fold increase in the area currently farmed. Our results therefore suggest that seaweed-based climate benefits may be feasible, but targeted research and demonstrations are needed to further reduce economic and biophysical uncertainties.

Offshore aquaculture has the potential to expand the macroalgal industry. However, moving into deeper waters requires suspended structures that will present novel farm-environment interactions. Here, we present a computational modeling framework, the Macroalgal Cultivation Modeling System (MACMODS), to explore within-farm modifications to light, seawater flow, and nutrient fields across time and space scales relevant to macroalgae. A regional ocean model informs the site-specific setting, the Santa Barbara Channel in the Southern California Bight. A fine-scale hydrodynamic model predicts modified flows and turbulent mixing within the farm. A spatially resolved macroalgal growth model, parameterized for giant kelp, Macrocystis pyrifera, predicts kelp biomass. Key findings from model integration are that regional ocean conditions set overall farm performance, while fine-scale within-farm circulation and nutrient delivery are important to resolve variation in within-farm macroalgal performance. Therefore, we conclude that models resolving within-farm dynamics can provide benefit to farmers with insight on how farm design and regional ocean conditions interact to influence overall yield. Here, the presence of repeating longlines aligned with the mean current generate flow diversions around the farm as well as attached Langmuir circulations and increased turbulence intensity. These flow-induced phenomena lead to less biomass in the interior portion of the farm relative to the edges. We also find that there is an effluent “footprint” that extends as much as 20 km beyond the farm. In this regard, MACMODS can be used to not only evaluate farm design and cultivation practices that maximize yield but also explore interactions between the farm and ecosystem in order to minimize impacts.

The ocean circulation around and over the Seychelles Plateau (SP) is characterized using 35 months of temperature and velocity measurements along with a numerical model. The results here provide the first documented description of the ocean circulation atop the SP. The SP is an unusually broad (∼200 km), shallow (∼50 m) plateau, dropping off steeply to the abyss. It is situated in a dynamic location (3.5–5.5°S, 54‐57°E) in the south‐western tropical Indian Ocean where northwesterly winds are present during austral summer and become southeasterly in austral winter, following the reversal of the western Indian ocean monsoon winds. Measurements around the Inner Islands, on the SP, have been carried out since 2015. Velocity measurements show that most of the depth‐averaged current variance on the SP arises from near‐inertial oscillations and lower‐frequency variability. Lower‐frequency variability encompasses seasonal and intraseasonal variability, the latter of which includes the effects of mixed Rossby‐gravity waves and mesoscale eddies. A global 0.1° numerical ocean simulation is used in conjunction with these observations to describe the regional circulation around the SP. Atop the SP, circulation is dominated by ageostrophic processes consistent with Ekman dynamics, while around the SP, both geostrophic and ageostrophic processes are important and vary seasonally. Stratification responds to the sea surface height semiannual signal which is due to Ekman pumping‐driven upwelling (related to the Seychelles‐Chagos Thermocline Ridge) and the arrival of an annual downwelling Rossby wave.

International climate goals require over 5 gigatons/year (Gt/year) of CO2 to be removed from the atmosphere by midcentury. Macroalgae mariculture has been proposed as a strategy for such carbon dioxide removal (CDR). However, the global potential for seaweed cultivation has not been assessed in detail. Here, we develop and use a dynamic seaweed growth model, the Global MacroAlgae Cultivation MODeling System (G-MACMODS), to estimate potential yields of four different types of seaweed worldwide, and test the sensitivity of these estimates to uncertain biophysical parameters under two nutrient scenarios (one in which the surface ocean nutrient budget is unaltered by the presence of seaweed farms, and another in which seaweed harvest is limited by nutrients that are resupplied by vertical transport). We find that 1 Gt of seaweed carbon could be harvested in 0.8% of global exclusive economic zones (EEZs; equivalent to ~1 million km2) if farms were located in the most productive areas, but potential harvest estimates are highly uncertain due to ill-constrained seaweed mortality and nitrogen exudation rates. Our results suggest that seaweed farming could produce climate-relevant quantities of biomass carbon and highlight key uncertainties to be resolved by future research.

Estimates suggest that over 4 gigatons per year of carbon dioxide (Gt-CO2 year−1) be removed from the atmosphere by 2050 to meet international climate goals. One strategy for carbon dioxide removal is seaweed farming; however its global potential remains highly uncertain. Here, we apply a dynamic seaweed growth model that includes growth-limiting mechanisms, such as nitrate supply, to estimate the global potential yield of four types of seaweed. We estimate that harvesting 1 Gt year−1 of seaweed carbon would require farming over 1 million km2 of the most productive exclusive economic zones, located in the equatorial Pacific; the cultivation area would need to be tripled to attain an additional 1 Gt year−1 of harvested carbon, indicating dramatic reductions in carbon harvest efficiency beyond the most productive waters. Improving the accuracy of annual harvest yield estimates requires better understanding of biophysical constraints such as seaweed loss rates (e.g., infestation, disease, grazing, wave erosion).

Net-zero greenhouse gas emissions targets are driving interest in opportunities for biomass-based negative emissions and bioenergy, including from marine sources such as seaweed. Yet the biophysical and economic limits to farming seaweed at scales relevant to the global carbon budget have not been assessed in detail. We use coupled seaweed growth and technoeconomic models to estimate the costs of global seaweed production and related climate benefits, systematically testing the relative importance of model parameters. Under our most optimistic assumptions, sinking farmed seaweed to the deep sea to sequester a gigaton of CO2 per year costs as little as $560/tCO2 on average, while using farmed seaweed for products that avoid a gigaton of CO2-equivalent greenhouse gas (GHG) emissions annually could return a profit of $30/tCO2-eq. However, these costs depend on low farming costs, high seaweed yields, and assumptions that almost all carbon in seaweed is removed from the atmosphere and seaweed products can displace products with substantial embodied non-CO2 GHG emissions. Moreover, the gigaton-scale climate benefits we model would require farming vary large areas (>100,000 km2)—a >40-fold increase in the area currently farmed. Our results therefore suggest that seaweed-based climate benefits may be feasible, but targeted research and demonstrations are needed to further reduce economic and biophysical uncertainties.

Baroclinic seamount‐trapped waves are thought to influence their surrounding ecosystem; however, trapped waves are not well‐studied in near‐equatorial settings, where stratification is strong and Burger numbers (S=N2H2f2LH2) are large. Motivated by observations, we use daily output (2005–2009) from the global Parallel Ocean Program Model (POP) to examine topographically trapped baroclinic waves around the Seychelles Plateau (S>400) in the tropical Indian Ocean. These trapped waves are associated with velocity and temperature oscillations at periods of 15–16 days, similar to the dominant period of some equatorial Yanai waves. Energy flux maps using POP output suggest that quasi‐biweekly equatorial Yanai waves excite trapped waves on the western and south‐western flanks of the Seychelles Plateau, near the surface. The anticyclonic energy flux associated with the trapped wave extends vertically throughout the water column and around most of the plateau circumference, diminishing on the eastern flank of the plateau. This work highlights the role that equatorial planetary waves and trapped waves play in facilitating energy redistribution, dissipation, and mixing in the tropical ocean.

In the version of this article initially published, in the Results subsection "Costs and benefits of large-scale seaweed farming", the percentages of ocean area farmed to reach 1 Gt and 3 Gt of CO 2 sequestered by sinking seaweed in the ambient nutrient scenario were incorrect due to typographical errors. As a result, in the sentence beginning "In the optimistic case", "0.85%" is now "0.110%", "310,000 km 2 " is now "400,000 km 2 ", and "Poland" now reads as "Zimbabwe". In the sentence following, "is slightly higher: 0.036% and 0.099%" now reads as "is 0.035% and 0.100%" and "$40" is now "$30". Furthermore, in the penultimate sentence of this paragraph, "ocean areas of 0.09-0.10% and 0.28-0.37%" now reads as "ocean areas of 0.085-0.100% and 0.285-0.410%" and "roughly 320,000-360,000 km 2 and 1,010,000-1,330,000 km 2 " is now "roughly 310,000-360,000 km 2 and 1,030,000-1,480,000 km 2 ".