Using a trait-based framework to characterize farmed seaweeds and guide selection of new candidates

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Seaweed farming has quietly become one of the fastest-growing sectors of global aquaculture, supplying food, hydrocolloids, fertilizers, animal feed, and emerging markets such as bioplastics and biofuels. Yet the industry’s expansion has been shaped less by systematic science than by tradition: farmers tend to cultivate the species they have always cultivated, and researchers tend to study the species that are already commercially dominant. A new perspective published in npj Ocean Sustainability argues that this inertia is holding the sector back, and that a trait-based framework borrowed from ecology and crop science could transform how candidate seaweed species are identified, compared, and selected for cultivation.

The core idea is deceptively simple. Rather than classifying seaweeds only by taxonomy or by their current commercial status, the framework characterizes each species by measurable functional traits: morphological features such as thallus size and branching, physiological features such as photosynthetic rates and nutrient uptake kinetics, and life-history features such as reproductive strategy and growth seasonality. In terrestrial agriculture, this trait-based approach has underpinned decades of crop improvement and ecological screening, allowing scientists to predict how a plant will perform under specific conditions without having to trial every individual genotype. The authors contend that seaweed science is now mature enough to apply the same logic, turning a scattered body of species-specific observations into a coherent, comparative discipline.

The need for such a framework becomes clear when one considers the structure of the seaweed farming industry. Global production is overwhelmingly concentrated in a handful of genera, including the kelp Saccharina and Undaria, the red algae Pyropia, Eucheuma, Kappaphycus, and Gracilaria, and the green alga Ulva. These cultivated species were largely domesticated from wild populations selected for availability and market demand rather than for optimized performance. Meanwhile, thousands of seaweed species remain uncultivated, many of which may possess traits, such as tolerance to warmer water, resistance to disease, rapid growth, or valuable biochemical compositions, that could make them superior candidates for future farming systems, particularly as ocean temperatures rise and cultivation expands into new biogeographic regions.

At the heart of the proposed approach is the recognition that no single trait determines success in aquaculture. A fast-growing species that cannot withstand wave exposure is a poor candidate for open-ocean farms; a hardy species with slow growth may never achieve commercial yields. Trait-based characterization allows these trade-offs to be made explicit. By compiling data on traits such as growth rate, temperature and salinity tolerance, nutrient requirements, epiphyte and pathogen susceptibility, ease of reproduction in hatcheries, and the mechanical properties of the thallus that determine how well a seaweed handles farm infrastructure, researchers can build comparative profiles that reveal which species are most likely to thrive under particular farming conditions and for particular markets.

The framework also speaks directly to one of the most pressing challenges in the field: climate resilience. Many of today’s workhorse species are cultivated near the thermal edges of their tolerance, and marine heatwaves have already caused significant crop losses in several producing regions. Selecting new candidates on the basis of thermal tolerance traits, rather than historical yield alone, could help the industry stay ahead of shifting ocean conditions. Similarly, as interest grows in offshore cultivation, where wave action and depth impose demands that nearshore farms do not, traits such as thallus robustness and attachment strength become decisive selection criteria that conventional species lists simply cannot capture.

Beyond environmental matching, trait-based screening can illuminate a species’ potential end-use. Seaweeds are farmed for wildly different purposes: nori for direct human consumption, carrageenan and agar-producing reds for hydrocolloid extraction, kelps for food ingredients and increasingly for applications in livestock feed and methane reduction. The biochemical profile of a species, its polysaccharide content, protein levels, pigment composition, and secondary metabolites, is itself a set of functional traits. Incorporating these biochemical characteristics into the framework means that candidate selection can be aligned with market opportunities from the outset, rather than discovering after years of agronomic development that a species is agronomically suitable but commercially unattractive.

The authors emphasize that building such a framework requires addressing significant data gaps. Trait information for seaweeds is patchy, fragmented across decades of phycological literature, and often measured with inconsistent methods that make cross-species comparison difficult. For many candidate species, even basic parameters such as maximal growth rate or reproductive biology in cultivation are unknown. The paper calls for coordinated efforts to standardize trait measurements, compile existing data into accessible databases, and prioritize trait characterization for species that show early promise. This is a familiar challenge in the history of trait-based ecology, where the value of comparative frameworks grew directly out of sustained investment in standardized measurement across research groups.

Another important dimension of the framework is its potential to support responsible innovation. Introducing new species into cultivation carries ecological risks, including the possibility of escapes, competition with native flora, and disease transmission. The authors argue that trait-based evaluation can incorporate risk-relevant traits, such as a species’ invasive potential, its reproductive dispersal capacity, and its host status for known seaweed pathogens, alongside performance traits. This integrated screening could help regulators and farmers distinguish between candidates whose domestication is ecologically prudent and those whose traits raise red flags, embedding biosafety into the earliest stages of candidate selection rather than treating it as an afterthought.

The social and economic geography of seaweed farming also figures in the analysis. A large share of global production occurs among smallholder coastal communities in Asia, and any expansion of the industry into new species and new regions will need to respect local capacities, infrastructure, and market structures. Traits such as the simplicity of a species’ cultivation cycle, the availability of seedstock, and the labor intensity of farm operations are directly relevant to whether a candidate species can be adopted by small-scale farmers. A framework that formalizes these practical traits alongside biological ones helps ensure that scientific selection translates into real-world adoption rather than remaining an exercise in laboratory optimization.

Looking forward, the trait-based approach opens doors to more quantitative and even predictive tools. As trait databases grow, statistical and machine-learning methods could identify combinations of traits that predict cultivation success, allowing researchers to screen large numbers of candidate species cheaply before committing resources to farm trials. The same data could guide selective breeding programs within promising species, identifying heritable traits that respond to improvement, much as crop breeders have done on land. In this sense, the framework is not merely a sorting exercise but a foundation for the deliberate domestication of a new generation of seaweed crops, bringing a level of intentionality to aquaculture that has so far been rare in the sector.

The broader significance of the work lies in its reframing of what seaweed farming could become. Today’s industry, for all its impressive growth, rests on a narrow biological base that is vulnerable to disease, climate shocks, and market fluctuations. Diversification is widely recognized as essential, but diversification without a principled selection process risks wasted investment and ecological harm. A trait-based framework offers a shared language for researchers, farmers, investors, and regulators to evaluate candidates systematically, compare trade-offs transparently, and prioritize the species most likely to succeed under the conditions of tomorrow’s oceans. As pressure mounts to expand sustainable marine food production, the ability to choose the right seaweed for the right place and purpose may prove to be one of the most consequential tools the industry acquires.

The analogy with terrestrial crop science is instructive because it highlights how long the payoff horizon for trait-based approaches can be. In agriculture on land, systematic trait screening preceded the green revolution’s yield gains by decades, and the seaweed sector is effectively at the beginning of that trajectory. Most cultivated seaweed genera have undergone little deliberate genetic improvement, meaning there may be substantial untapped potential even within currently farmed species once their traits are properly quantified and compared.

The framework also arrives at a moment when demand for seaweed products is diversifying beyond traditional food uses. Emerging applications, from biostimulants to alternative proteins, each favor different biochemical and physiological profiles, which strengthens the case for matching species to end-use through explicit trait data rather than trial and error. A species rich in specific polysaccharides, for example, may justify cultivation under conditions that would be uneconomical for a general-purpose food crop.

Finally, the perspective underscores a cultural shift within phycology itself. Much existing knowledge of seaweed biology resides in ecological studies of wild populations rather than in agronomic trials, and the proposed framework offers a route to translate that ecological understanding into cultivation insight. By treating traits as the common currency between wild ecology and farm performance, researchers can begin predicting how uncultivated species might behave in farm settings before expensive domestication programs begin, potentially shortening the path from ocean to aquaculture for promising new candidates.

Subject of Research: Using a trait-based framework to characterize farmed seaweeds and guide selection of new candidates

Article Title: Using a trait-based framework to characterize farmed seaweeds and guide selection of new candidates

Article References: Fong, C. R., Fong, P., & Froehlich, H. E. (2026). Using a trait-based framework to characterize farmed seaweeds and guide selection of new candidates. npj Ocean Sustainability. https://doi.org/10.1038/s44183-026-00239-5

Image Credits: AI Generated

DOI: 10.1038/s44183-026-00239-5

Keywords: trait-based, framework, characterize, farmed, seaweeds, guide, selection, candidates, scientific research