Defining and finding the profit for seaweed secondary extensive aquaculture

Abstract

Seaweed aquaculture is expanding globally, yet small-scale producers, such as those emerging in the United States, face challenges in achieving economic viability. We introduce and formalize the concept of secondary extensive aquaculture (SEA): the non-target cultivation, harvest, and use of extractive species (e.g., seaweeds) that naturally recruit and grow on existing aquaculture infrastructure designed for a different primary species (e.g., oysters). To explore the economic viability of SEA, we employed a scenario-based bioeconomic modeling approach, coupling logistic seaweed growth and sustainable harvest with a simple profit function. The model was parameterized with literature-derived ranges for seaweed growth and carrying capacity, as well as data from a 2025 pilot harvest on a 65 ha oyster farm in California. Using simulations, we evaluated key ecological and economic combinations under which seaweed SEA may offset the estimated 5-10% production losses associated with typical, unharvested biofouling. We showed that profitability increased with farm size, growing season length, and intrinsic growth rate (r) of seaweed, with viable scenarios typically requiring > 50-100 ha and > 60 growing days under conservative market assumptions ($400 t^-1 wet weight). Intrinsic growth rate exerted a stronger influence on profitability than carrying capacity (K), indicating that faster-growing seaweed species (e.g., Ulva spp., Gracilaria spp., and Pyropia spp.) are more suitable candidates for SEA. In fact, modal ecological conditions on a 65 ha farm may offset biofouling costs. Labor intensity, however, emerged as a major bottleneck, with pilot-informed labor estimates (~140-200 hrs. t^-1 including processing) far exceeding the ca. 10 hrs. t^-1 needed to breakeven at minimum wage, but could be achieved with realistic improved efficiency. Although our pilot SEA yields fell near the lower bound of global seaweed aquaculture production, they remain within plausible commercial ranges. Overall, SEA represents a promising complementary strategy for diversifying revenue streams and enhancing circularity in aquaculture systems, but its realization will depend on sufficient scale, favorable biological productivity, labor efficiency improvements, and supportive policy frameworks.

Introduction

Seaweed aquaculture is of growing interest in many countries around the world, including the United States (U.S.) (Krak, 2021; Heidkamp et al., 2022). Millions of tons of seaweed are produced every year for the estimated $12.4 billion (USD) market (FMI, 2025), the majority (97%) coming from Asia and largely used for human consumption as direct food, thickening, or clarifying agents (Piconi et al., 2020; FAO, 2021, 2024; Zhang et al., 2022). However, in such a globalized market, small-scale producers – likely the majority of current U.S. farm operations – are struggling to find the right market pathway to be profitable at a smaller scale (Kotowicz et al., 2024; Angera, 2026). This is particularly challenging for regions where only small-scale farms are socially preferred (e.g., California) (Fong et al., 2024b). One potentially innovative strategy is harvesting settled seaweed off already profitable shellfish farms.

Aquaculture operations in open environments consistently contend with “biofouling” and “nuisance” seaweeds (Bannister et al., 2019). Biofouling is the settlement and growth of normally unwanted species on aquaculture organisms and/or infrastructure (Bannister et al., 2019). Problems caused by the competition between the biofouling species and cultured species for space, light, and nutrients have been estimated to cost 5-10% of all production (Lane and Willemsen, 2004) or more (Fitridge et al., 2012). Species and severity of impact can vary, but seaweeds commonly accumulate on farms and can directly cause shell erosion, stock loss, and smothering (Bannister et al., 2019). Interestingly, some of the nuisance algae are species also actively farmed in aquaculture, including Gracilaria spp., Porphyra/Pyropia spp., and Ulva spp. (Bannister et al., 2019). Given that this biological material must be removed for the benefit of the primary crop, exploring what economic and ecological considerations make intentional harvest of the seaweed(s) profitable may be an important addition to the growing research into seaweed potential for the blue economy.

We propose the formalization of secondary extensive aquaculture (SEA). Informed by the definitions of new and existing aquaculture practices (Froehlich et al., 2017; Mizuta et al., 2022), we define SEA as “the non-target cultivation, harvest, and sale or use of extractive species (e.g., seaweeds) that naturally recruit and grow on existing aquaculture infrastructure used for farming a different primary species (such as oysters or clams),” (Figure 1a). We contend SEA satisfies the definition of aquaculture used by the Food and Agriculture Organization of the United Nations (FAO) and the European Union (EU) as “farming,” which requires (i) some intervention in the rearing process and (ii) ownership of the stock throughout rearing [FAO Fisheries Glossary; Regulation (EU) No. 1380/2013, Art. 4(25)]. Placement and maintenance of the primary aquaculture infrastructure (e.g., longlines, bags) constitute the intervention: it provides artificial hard substrate and alters local water flow, structuring where and how much seaweed recruits and grows relative to an unmanaged wild population. Ownership is likewise satisfied, since recruiting seaweed grows for its entire rearing period on privately leased and actively managed infrastructure, analogous to how low-intervention, extensive systems such as traditional Hawaiian fishponds (loko i‘a) have long been recognized as aquaculture despite relying on tidal recruitment of wild fishes or crustaceans through sluice gates rather than active stocking or feeding (Costa-Pierce, 2022). This infrastructure-mediated model of ownership and passive intervention is consistent with the broadened conceptualizations of aquaculture proposed by Froehlich et al. (2017) and Mizuta et al. (2022), who argue aquaculture definitions should extend beyond food-focused, high-intervention systems to encompass practices that repurpose existing infrastructure and natural recruitment toward ecological or secondary economic ends. In addition, equivalent approaches for wild plants are reported in agriculture (FAO, 1999), but similar considerations appear largely undefined and missing from aquaculture (exception: Arduini et al., 2026). As such, SEA may provide a mechanism through which existing intensive/semi-intensive aquaculture operations can exploit seasonal biofouling as an additional harvestable crop. Note, however, that SEA relies on species that recruit naturally rather than being seeded, and thus farmers have less direct control over which species colonize their infrastructure. SEA profitability is therefore contingent on the species assemblage a given farm happens to support, meaning farm suitability, rather than species selection, is the relevant management lever.

Figure 1

At scale, species like Gracilaria (red algae; also known as ogo or sea moss) have been most commonly farmed for agar, Pyropia (red algae; also known as nori) garners higher value as direct-to-consumer sushi-grade seaweed, and Ulva (green algae; also known as sea lettuce) has a range of applications, including use in feeds due to its moderately high protein content (Santelices and Doty, 1989; Janke, 2024) (Figure 1b). However, a suite of new and scale-appropriate markets is being explored and developed, including biostimulants (Janke, 2024). Marine-based biostimulants – soil additives that can improve terrestrial agricultural yields and possibly lower emissions compared with fertilizers – appear to hold particular promise for smaller-scale farms (Lodhia, 2023; Linsmayer and Gardner, 2025), and perhaps even more so as a secondary economic stream given the typically lower price point ($0.10-0.30 USD per lb or $0.22-0.66 per kg). While the focus of this research is not explicitly on the market pathway of biostimulants, the lower biostimulant price point provides a useful lower bound for potential revenue streams in our model scenarios. More specifically, smaller-scale, more local-regional supply chains may be the ideal market pathway for SEA harvest and create a more sustainable aquaculture system overall.

Using a management strategy simulation-based approach (Punt et al., 2016), we explored under what economic and ecological conditions SEA of seaweeds may be a value add to an existing aquaculture farm, particularly whether it can recoup the 5-10% losses associated with biofouling reported in the literature. Using a simple, generalized bioeconomic modeling method, paired with parameter synthesis and in situ measures from a real-world SEA pilot effort, we addressed four specific objectives: (1) determine how farm size and growing season length affect SEA profitability across a range of seaweed growth rates (r) and carrying capacities (K); (2) identify labor and wage conditions required to achieve profitability, informed by real-world pilot harvest and processing data; (3) evaluate whether our pilot-informed SEA yields can offset the reported 5-10% biofouling losses under realistic market prices; and (4) compare pilot and modeled SEA yields relative to global seaweed aquaculture production. Through this exploratory, scenario-modeling approach, we begin to understand what conditions likely make SEA a viable new economic pathway for the aquaculture industry.

Methods

We employed a generalized bioeconomic model to simulate seaweed co-production within an existing oyster aquaculture operation, treating farmed seaweed biomass as a renewable biological stock subject to essentially wild harvest. Traditional extensive aquaculture more closely resembles harvesting from the wild, allowing application of fundamental fisheries-based modeling approaches. We specifically paired a generalized simulation framework with an empirical case application, which is common practice in fisheries modeling, particularly for data-limited systems, where a model is developed alongside a real-world case to ground assumptions and parameters that are otherwise not available (Punt et al., 2016).

Seaweed production was represented using a surplus-production (logistic) model with proportional harvest, a widely used approach to evaluate maximum sustainable yield (MSY) and harvest strategies (Tsikliras and Froese, 2019). Biomass dynamics were simulated at a daily time step over a 20-year horizon to capture long-run equilibria. The MSY was derived from the surplus-production model and used to define biologically sustainable harvest and equilibrium biomass levels. We assessed economic outcomes by linking equilibrium and dynamic harvest levels to a profit function that accounts for market price, variable production costs, labor inputs, and fixed operating costs. We tested these metrics assuming a semi-intensive oyster farm, where oysters are grown on longlines to market size within enclosed baskets with stocking densities > 100 individuals per basket (Olin et al., 2012). Oyster production was specifically treated as an exogenous baseline activity, allowing seaweed profitability to be interpreted as an incremental gain (or loss) from diversification. Thus, a simplifying assumption is that oyster revenue/cost (Table 1, $100,000/$80,000 per ha/yr) is fixed, encompassing the modeled farm’s maintenance and daily activities (e.g., frequency costs of cleaning biofouled lines). We instead focused on explicitly modeling seaweed growth and potential added profitability.

Ecological model

For an average oyster farm design, a discrete seaweed standing biomass (B_t tons of wet weight) at time t on the farm was represented with a logistic production model with proportional harvest removals:

where r is the intrinsic rate of biomass increase, K is the farm-scale carrying capacity, and h is the instantaneous harvest rate, all represented at a daily time step (Δt = 1/365 yr; Equation 1). A daily time step was selected because most relative growth rates of seaweeds are reported at that scale. Carrying capacity (K) represents the maximum standing wet biomass per hectare that farm infrastructure and prevailing local conditions (e.g., light, nutrient supply, substrate/line space, water flow) can support; we did not mechanistically model these environmental drivers, but instead drew empirical, species- and site-specific K estimates directly from the literature (Table 1, 10-100 t ha^-1), reflecting realized standing biomass under a range of real-world farm and environmental conditions.

Given the logistic equation, maximum sustainable harvest rate (h_MSY), biomass (B_MSY), and yield (H_MSY) were calculated:

Annual harvest (H) was obtained by summing daily removals, and MSY served as the model-derived upper bound on sustainable harvest within the logistic framework (Equation 2); sustained extraction above this level would drive the modeled population(s) toward depletion, though in practice external recruitment and seasonal settlement from surrounding fouling communities likely buffer against permanent collapse and may allow biomass to recover within subsequent growing seasons. Harvest was thus modeled as continuous removal (h) rather than as a fixed number of discrete events or individual harvest trips. Instead, labor (l) and variable costs (c_s) are expressed per ton harvested (Equation 3, see below), so any realized harvest schedule (e.g., weekly, biweekly) sums to approximately the same annual harvest, yielding equivalent total labor cost and profit.

While multiple wild seaweeds do grow simultaneously on a farm, we assumed a batch harvest (i.e., harvested together) and explored the impact on SEA when more or less r-selected (faster growing; e.g., Ulva) versus K-selected (slower growing; e.g., kelps) species grow under different ranges of carrying capacity. Note that ‘slower’ is relative to other seaweeds; kelps are still very productive compared with animals. We assessed outcomes over a range of these ecological parameters given the uncertainty and likely context dependence of any given farm. The terms r- and K-selected refer to classical life-history theory (MacArthur and Wilson, 2001), a framework in which the terms themselves derive from the logistic growth model. These labels are used only as biological shorthand to help interpret the ecological range explored (e.g., Macrocystis, included in our literature search terms, represents the slower-growing/higher-K end of the spectrum), rather than as discrete categories formally compared in the analysis; profitability was instead evaluated continuously across the full literature-derived ranges of r and K (Table 1), independent of species identity or life-history category. Looking at the relative impact of r and K over an array of values allows for broader exploration of SEA and its limitations depending on what species tend to dominate on an aquaculture operation, without being prescriptive.

Economic model

Seaweed was treated as a co-product integrated into an oyster farm. Annual seaweed profit П_S was computed from revenues minus variable and fixed costs:

where H_S (t yr^-1) is annual seaweed harvest, P_S (USD$ t^-1) is the realized seaweed price (combined across product streams, e.g., Ulva for biostimulant and nori for restaurant markets), c_S ($ t^-1) is non-labor variable cost per ton, w ($ hr^-1) is the effective wage rate, l (hr t^-1) is incremental labor required per ton attributable to seaweed (harvest + processing beyond baseline oyster operations), and F_S(USD$ yr^-1) is annual seaweed-specific fixed cost. Note that we did not apply a fixed compositional ‘blend’ weighting between product streams to compute P_S; rather, price was varied across the full literature-derived range ($400–$1,200 t⁻¹, Table 1), with the lower bound reflecting biostimulant/bulk wet-biomass pricing and the upper bound reflecting nori/restaurant-grade pricing, so that scenarios spanning either market (or any realistic mix of the two) fall within the explored range.

In the daily model, as in the seaweed model, variable revenue and costs were computed on each day using daily harvest and then summed annually; fixed costs were allocated evenly across days (i.e., F_S/365 per day). Oyster profit was treated as the primary constant commodity baseline for relative profit inference. Importantly, we assume the original costs to clear the biofouling do not disappear but instead are redirected to harvest.

To identify conditions under which co-produced seaweed becomes profitable, we evaluated seaweed profit across a range of wage rates (w) and incremental labor requirements (l), holding biological harvest H_S fixed at the steady-state annual harvest from the dynamic model and calculating the breakeven combinations (П_S = 0).

Parameters

A series of parameter values was aggregated based on existing literature (Table 1). A literature search of gray and white documents and websites was conducted using Google Scholar, Google Gemini, and ChatGPT Research AI. All documents were verified by a human. For the ecological model we searched for documents on “ulva”, “nori”, “pyropia”, “porphyra”, “gracilaria”, “macrocystis”, “relative OR standard growth rate”, and “carrying capacity”. These terms gave a suite of values to inform the upper, lower, and average growth rates and carrying capacities of relatively slower (K-selected) and faster (r-selected) growing species. Next, we searched for “aquaculture OR farmed”,”seaweed”, “oyster”, and “market analysis OR assessment” to help bound realistic values for our economic model. Within these results, the lower end of the price range ($400 t⁻¹) draws primarily from biostimulant and bulk/wholesale wet-biomass market data (Lodhia, 2023; World Bank, 2023; TRIDGE, 2025) while the upper end ($1,200 t⁻¹) reflects nori and other restaurant/edible-grade market prices (Hwang and Park, 2020; Piconi et al., 2020; Brayden and Coleman, 2024; FMI, 2025), consistent with the two product streams (seeEquation 3); Kite-Powell et al. (2022) informed cost benchmarks across both.

A pilot SEA effort was also performed April 23 and 29, 2025 on the Hog Island Oyster Tomales Bay farm (ca. 65 ha) in Northern California to estimate an initial baseline for labor hours and wet-weight harvest. The first harvest on the 23rd was performed by three individuals, while the second on the 29th was performed by six people. Gracilaria (ogo) was harvested off of bottom bags and Pyropia (nori) was harvested off suspended SEAPA gear and lines, then processed for Hog Island restaurants. The results allowed us to test a real-world SEA collection effort, both in harvest and labor efficiency.

Analysis

Given SEA harvest is not yet an established or formally reported technique in the literature, there is tremendous uncertainty surrounding the additional costs to the farm (fixed and labor). Using a stepwise scenario-based approach, we first simulated the profitability potential across a range of ecological and economic parameters to then inform a more bounded, realistic farm scenario.

We first evaluated profitability (П_S > 0) and breakeven (П_S= 0) space across farm size and growing season (30-150 days), reflecting the seasonal nature of seaweed production. We assumed harvest at MSY under three (additional) annual fixed cost scenarios (F = $1,000, $10,000, and $20,000 yr^-1) and across reported seaweed r and K values to represent more (larger r and/or K) or less (smaller r and/or K) productive seaweed populations/species, including use of modal values as moderate ecological conditions to accommodate the skewed nature of the data (Table 1). Intrinsic annual growth rates were derived by log-transforming daily percent grow values from the literature and multiplying by the growing season length. Additional non-labor fixed costs not already covered by oyster operations may include seaweed-specific equipment, storage, and permitting. We assumed minimum wage labor ($16.90 hr^-1), 10 labor hours per ton, and a baseline wet-weight price of $400 t^-1, reflecting emerging market conditions. To examine price sensitivity, we also evaluated a moderate scenario at $1,200 t^-1 (typical of nori). Together, these scenarios quantified profit potential under ecological and market uncertainty.

While the exploratory modeling provided a broad view of profitability across parameters, we were interested in assessing the profit potential based on the real-world pilot SEA efforts. Using the pilot line yields and assuming 8,000 m of line per hectare (Table 1), we identified a combination of r and K values that may result in equivalent line (MSY) yield. Using those pilot-informed ecological parameters, we re-ran the bioeconomic model assuming a 65 ha farm (equivalent to the sampled Hog Island Tomales Bay lease area), moderate additional fixed costs (F = $10,000 yr^-1), and again the more conservative price ($400 t^-1). We then calculated the minimum labor hours required under California minimum wage conditions ($16.90 hr^-1) to breakeven (П_S= 0), and assessed the proportional profit to the entire (oyster + seaweed) system to discern if SEA may offset reported (5-10%) biofouling costs.

We next evaluated whether the labor demands and yield requirements identified under the ‘real-world’ breakeven were achievable and how they compared with more intensive seaweed farming systems. We specifically assessed feasibility using two efficiency-improvement scenarios (50% and 80% reductions in labor-hours per ton). These bounds were informed by the 1275% (ca. 14-fold) increase in labor efficiency documented for the Maine seaweed sector over a 5-year period (Brayden and Coleman, 2024), equating to a compound annual reduction in labor-hours per unit harvested of approximately 41% yr⁻¹. Note that this labor-reduction benchmark reflects efficiency gains across the full production cycle (i.e., gear installation, seeding, maintenance, and harvest), whereas we only account for harvest and processing improvement. Thus, to assess short-term viability of a reduced aspect of farming, we assumed 50% and 80% reductions that may theoretically be achieved in about one to three years, respectively.

Finally, we compared observed and estimated farm-level yields (pilot and MSY) to production levels reported from more intensive global seaweed aquaculture systems (Fong et al., 2024a) to contextualize the scale of SEA. We specifically compared the pilot and estimated MSY yields (tons per ha per yr) of this study to the median, lower (Q1), and upper (Q3) quartiles at the country and experimental levels from the global standing literature.

Results

Minimum farm size and seasonal profitability

Not surprisingly, profitability increased with both farm size and growing season, with larger farms and longer seasons consistently reducing the minimum area required to breakeven (Figures 2a–f). Across most scenarios, shorter growing seasons (< ca. 60 days) required disproportionately larger farm areas to achieve positive returns, whereas extended seasons substantially lowered the breakeven threshold. Under moderate (modal) ecological conditions (e.g., r = 0.02 t day^-1, K = 20 t ha^-1), profitable outcomes were only attainable at larger farm sizes (> 100 ha), unless seasons were long (Figure 2b); even then, the farm size needed to be > 50 ha. In contrast, very slow growth (r_min = 0.001 t day^-1) and very low carrying capacity (K_min = 10 t ha^-1) resulted in only negative profits regardless of farm size (Figure 2d), highlighting that some ecological conditions preclude economic feasibility altogether.

Realistic, faster intrinsic growth (higher r) reduced breakeven farm size more strongly and created higher profit potential than increasing carrying capacity (higher K), while the highest price point outperformed lower fixed costs. Scenarios with higher r substantially expanded the profitable region even when K remained moderate, whereas increasing K without faster growth produced more modest gains (Figures 2a, c). Indeed, the maximum possible profit under max r (Figure 2a) was more than 500% higher than that of max K (Figure 2c). In practice, however, farm size and fixed costs function as the primary management levers in extensive systems. Higher fixed costs (e.g., $20,000 yr^-1) shifted breakeven upward, requiring substantially larger farms to offset overhead, while lower fixed costs expanded the range of viable farm sizes (Figures 2e, f). Assuming a higher price of the seaweed for the modal farm (Figure 2b scenario with $1,200 t^-1 instead of $400 t^-1) resulted in all farm sizes and lengths of seasons to be profitable.

Figure 2

Feasibility and minimum wage labor

The April 2025 pilot harvests demonstrated both the technical feasibility of SEA-based nori production and the substantial labor intensity (at least initially) required at smaller scales. The 23 April mock harvest produced ~22.7 kg of wet nori in 19 minutes with three people (57 total labor-minutes), equivalent to ~42 labor-hours per ton for harvest and ~198 labor-hours per ton for processing. The 29 April group harvest (six people) yielded ~104 kg of total wet biomass (86 kg nori + 18 kg ogo), corresponding to ~62 labor-hours per ton for harvest and ~142 labor-hours per ton for processing. Assuming 8,000 m of line per hectare, the three-person collection represented 0.083 kg of wet weight per meter of line and the six-person collection 0.138 kg of wet weight per meter. Across both efforts, harvest labor averaged ~50–60 hrs. per ton, whereas processing ranged more widely (~140-200 hrs. per ton), making post-harvest handling the primary labor bottleneck.

Using pilot line yields as a reference and assuming 8,000 m of line per hectare across a 65 ha farm, the total line length required to achieve MSY-equivalent production declined steeply as yield per meter increased (Figure 3a). At very low line yields, the required line length exceeded several thousand kilometers – clearly infeasible – whereas modest increases in line yield sharply reduced the necessary infrastructure. Under pilot-informed yields, we showed that the hypothetical MSY-equivalent harvest (line yield = 0.117 kg m^-1; total annual yield = 61 t yr^-1) may correspond to r = 0.005 t day^-1 and K = 5 t ha^-1 (~500 km total line). While it is highly uncertain if the pilot SEA harvest was operating near MSY, the combination allows exploration of profitability in a real, less productive system.

Figure 3

Based on the pilot-informed ecological parameters (r = 0.005 t day^-1 and K = 5 t ha^-1) and again assuming a 65 ha farm, $10,000 yr^-1 additional fixed costs, and a $400 t^-1 price, breakeven profitability was highly sensitive to labor requirements (Figure 3b), and SEA accounted for only ~1% of total (oyster + seaweed) profit. At California minimum wage ($16.90 hr^-1), the farm would need to limit total harvest and processing time to ca. 10 labor hours per ton to breakeven. The breakeven curve illustrates the tradeoff between wage levels and labor efficiency: higher wages require substantial reductions in labor hours per ton to maintain viability. In addition, the gains were well below the 5-10% biofouling costs. That said, with a higher seaweed value ($1,200) or moderately better ecological condition (r = 0.02 t day^-1 and K = 20 t ha^-1), SEA accounted for 4% to 11% of total profit, respectively, successfully recouping comparable biofouling (5-10%) losses.

Increasing the crew from three to six people during the pilot SEA harvest reduced labor hours by ca. 30% but was insufficient to meet breakeven (10 hr t^-1) and underscored the importance of labor efficiency improvements (Figure 4). Assuming the relationship holds as the number of people increases, we showed that under the no-technological improvements scenario, labor demands remained high even with additional personnel, decreasing gradually from ~200 labor-hours per ton with three workers to ca. 48 hours per ton with 15 workers. Incorporating a 50% efficiency improvement substantially reduced labor intensity across all crew sizes, with breakeven achieved only at higher staffing levels (ca. 15 workers). In contrast, an 80% efficiency improvement led to a steep reduction in labor requirements, reaching the breakeven threshold with comparatively few workers (ca. 8 people) and approaching negligible labor-hours per ton at larger crew sizes. Labor-hours per ton reflects total crew effort normalized by harvest weight (i.e., summed person-hours divided by tons harvested); the observed reduction with crew size reflects task parallelization (e.g., simultaneous harvesting, bagging, and transport). This relationship follows a decay function, such that each additional worker contributes progressively smaller reductions in per-ton labor, asymptotically approaching a floor rather than continuing to decline indefinitely. These results indicate that technological efficiency gains, including improved knowledge, are more influential than incremental increases in crew size for achieving labor-feasible and profitable SEA production.

Figure 4

SEA scale

The pilot SEA total wet weight yields (three people = 0.664 t ha^-1 yr^-1; six people = 1.10 t ha^-1 yr^-1) and estimated hypothetical MSY (0.938 t ha^-1 yr^-1) fell near the lower bound of reported global seaweed aquaculture production (Figure 5) (Fong et al., 2024a). While both experimental and country-level yields tend to be at least 30 to 60x higher, respectively, the SEA pilot yields were 2-3x higher than the minimum reported in the literature (0.28 t ha^-1 yr^-1) (Yang et al., 2015) – a country-level yield reported for a Gracilaria monoculture in China, likely a line system (Fong et al., 2024a). This value represents the single lowest yield among the 190 algae estimates compiled in the global systematic review of dedicated seaweed aquaculture producers and thus reflects the observed floor of documented commercial seaweed production. In fact, the vast majority (85%) of seaweed aquaculture yields < 5 t ha^-1 yr^-1 were associated with Ulva, Pyropia, and Gracilaria, although stemming from a single study in China (Gao et al., 2022). Regardless, this indicates SEA harvest falls within the plausible bounds of dedicated seaweed aquaculture, which is promising for the viability of the approach.

Figure 5

Discussion

Secondary extensive aquaculture (SEA) represents an ecologically feasible but perhaps economically constrained approach to harvesting seaweed from existing aquaculture infrastructure, with pilot yields falling within the lower bounds of reported seaweed aquaculture production. Profitability depended strongly on farm size and growing season length, with most viable scenarios requiring longer seasons (> 60 days) and larger farms (> 50-100 ha), likely limiting feasibility for smaller operations. Ecological productivity, particularly intrinsic growth rate (r), also played a key role, indicating that faster-growing fouling species are more likely to support economically viable harvests. However, labor intensity emerged as the primary operational bottleneck, with pilot-informed labor requirements far exceeding breakeven thresholds under minimum wage conditions. That said, modal ecological conditions and/or higher prices may offset the potential losses of biofouling removal (5-10%). Together, these findings suggest SEA is best viewed as a complementary strategy whose economic viability will depend on sufficient scale, favorable ecological conditions, and improvements in labor efficiency.

Economic feasibility of SEA was strongly constrained by farm size and growing season length, with profitable outcomes generally requiring sufficient growing seasons (> 60 days) and larger farms (> 50-100 ha, scenario dependent) under typical ecological and market conditions. Many farmed seaweed species are harvested multiple times a year (i.e., re-harvest), and our growing season requirements were consistent with these trends (e.g., Redmond et al., 2014; FAO, 2026). We were also able to identify important size thresholds necessary for SEA profitability, showing that an average small-scale (marine) aquaculture farm (mean ± SD = 1.23 ± 1.55 ha) (Sierra Castillo et al., 2026) is less likely to benefit from such an approach and simply removing biofouling seaweed species is likely a better option financially. That said, smaller family-run or community-supported farms may have some advantage given additional SEA labor may be largely voluntary (w_min = 0) (Sierra Castillo et al., 2026) – though that can occur for larger farms too if family operated (e.g., Brayden and Coleman, 2024), which opens the opportunity for some profit if the other factors are favorable, including species ecological parameters.

Realistic intrinsic growth rate (r) exerted a stronger influence on profitability relative to carrying capacity (K), highlighting that biological productivity, rather than standing biomass alone, is an important ecological factor to consider for the economic viability of extensive seaweed systems. Seaweeds are generally known for very high growth rates, but our study showed that within that group of algae, r-selected species are more likely to support a SEA strategy. This includes organisms we have already highlighted, including species of Ulva (Pérez-Mayorga et al., 2011), Gracilaria (Yang et al., 2006), Pyropia (Green and Neefus, 2016), and Palmaria (Lukeman et al., 2012). This emphasizes the importance of a farmer having at least a general idea about what wild species or genus is fouling the farm to inform potential productivity. Conveniently, seaweed traits such as intrinsic growth rate have very recently garnered more attention in ecology (Fong et al., 2025; Smith et al., 2025), which may help identify candidate species and farms suitable for SEA more broadly. Of course, measuring farm-specific daily growth would improve certainty of any profitability assumptions. In the absence of such measures, however, we showed that simply knowing the growth tendencies of fouling species improves the chances of SEA being profitable.

Labor intensity represents the most critical operational bottleneck to profitability, with pilot-informed conditions requiring an approximately 20-fold reduction in labor hours per ton to achieve breakeven under minimum wage assumptions. Indeed, the bulk of costs a seaweed farm may have can be attributed to labor (Kite-Powell et al., 2022; Brayden and Coleman, 2024). As previously mentioned, family or community voluntary hours can bring down wage costs, but so can general improvements in efficiency. We showed that technological and/or knowledge-driven improvements are more effective than increasing crew size alone in reducing labor requirements, underscoring innovation and process optimization as essential pathways toward economic feasibility of SEA. These improvements can happen through repeated practice, training, retention of knowledgeable staff, clear protocols (i.e., Standard Operating Procedures), and specialized equipment (De Silva et al., 2001; Lawrence et al., 2023; Suresh, 2023). Importantly, efficiency improvements we explored (50% and 80%) appear exceedingly conservative based on a reported 1275% increase in labor efficiency for Maine seaweed farms between 2017 and 2022 (Brayden and Coleman, 2024), and given our pilot efforts were not focused on speed but process. The authors also showed a strong positive correlation between farm size and labor efficiency, further supporting our results that larger farms (> 50-100 ha) are likely better candidates for SEA.

Several important caveats should be considered when interpreting the results of the first exploratory paper concerning SEA. First, many parameters – including growth rates, carrying capacities, yields, and labor efficiency – were based on limited pilot observations, existing literature, and model assumptions, and thus may not capture the full range of variation across seasons, species, farms, and environmental conditions. Second, our analysis assumed stable economics, yet seaweed markets remain emerging and volatile, and future increases in price, technological improvements, and/or policy incentives (e.g., subsidies) may substantially alter economic feasibility. Third, we evaluated SEA largely as a standalone revenue stream, whereas in practice its value may also include indirect benefits, such as higher overall reduction of biofouling from SEA activities compared with typical cleaning regimes resulting in improved primary crop production, which was not explicitly monetized here. We assumed stable oyster production, with costs being absorbed by active harvest of seaweeds instead of biofouling removal; but more explicitly exploring feedbacks on oyster growth and profit is a logical next step to this study. In addition, we only focused on macroalgae, but biofouling invertebrates (e.g., mussels) may offer different SEA-like opportunities (e.g., Arduini et al., 2026). Finally, our results are most applicable to extensive, opportunistic systems and do not necessarily translate to dedicated seaweed aquaculture that operates under different social-ecological considerations (e.g., hatcheries, active seeding of lines, strain selection). As SEA relies on natural recruitment rather than seeding, farmers have less direct control over which species settle on the lines and structures, a farming limitation common to more traditional extensive (i.e., low intervention) practices (Costa-Pierce, 2008). Thus, farm siting may have an outsized role in shaping recruiting assemblages. As a result, species composition will likely vary over time, affecting labor needs and potentially complicating market strategy (e.g., a biostimulant market may be more resilient to species variation than a nori-only market). Quality and safety are also essential, and protocols need to be established, building off existing approaches of the seaweed industry (e.g., Concepcion et al., 2020).

Actually realizing the potential of secondary extensive aquaculture (SEA) will require coordinated advances in policy, research, and industry practice to reduce uncertainty and improve economic feasibility. Future research should focus on measuring (and validating) species-specific growth dynamics on different farms, identifying high-productivity candidate species, and developing technologies and protocols that substantially reduce labor intensity. What species are growing on a given farm and what new viable organisms are present are ripe for investigation. Industry efforts can also accelerate progress through pilot commercialization, knowledge sharing, and investment in specialized equipment and workforce training, which have already demonstrated dramatic efficiency gains in emerging seaweed sectors (Brayden and Coleman, 2024). Policy can also play a critical role, in particular by clarifying and reducing costs for permitting pathways for co-harvested species (e.g., van Senten et al., 2020). Together, such efforts may help transform SEA from an opportunistic byproduct into a scalable, economically viable strategy that diversifies revenue streams and contributes to more sustainable aquaculture systems in the future.

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