Aquaculture's role in achieving UN Sustainable Development Goals (SDGs) related to food security (SDG 2), climate change (SDG 13), and biodiversity (SDG 14) is significant. Global aquatic species consumption has nearly doubled since 1961, with seafood providing essential protein for billions. Aquaculture production has become crucial, especially as capture fisheries have plateaued. However, climate change poses challenges to aquaculture through ocean warming, acidification, and extreme weather events, impacting productivity and food security. Additionally, aquaculture can negatively impact biodiversity through habitat destruction, disease transmission, and overfishing for feed. This study addresses the need for a biologically informed assessment of aquaculture's contribution to FCB goals by focusing on the traits of farmed species and their influence on sustainability.

The study conducted a systematic literature review to identify traits of farmed aquaculture species related to FCB objectives. The review followed the PRISMA statement protocol, focusing on publications discussing biological or ecological characteristics of farmed species in relation to FCB. The review identified and categorized traits related to food security (production potential, nutrient availability), climate change (environmental tolerance, climate change mitigation), and biodiversity (invasiveness, benefits to local biodiversity). The review revealed a significant number of traits associated with food security, with a substantial overlap with climate change and biodiversity traits, suggesting potential co-benefits.

A fuzzy logic expert system was developed to quantify the potential of aquaculture species to contribute to FCB goals. This approach uses fuzzy set theory to handle uncertainty and data gaps. The methodology involved three steps: 1. **Fuzzification:** Trait values were assigned to linguistic categories (low, medium, high, very high) using trapezoid and triangular membership functions. These functions defined the degree of membership of each trait value to each category, accounting for uncertainty. Missing data was penalized by assigning it to the 'low potential' fuzzy set. 2. **Fuzzy Reasoning (rule-firing):** Heuristic rules, derived from the literature, linked traits to FCB potential. Rules were fired if the membership level exceeded a threshold (0.2). The MYCIN accumulation algorithm combined conclusions from multiple traits to obtain the final degree of membership to each linguistic category for each species. All rules were given an equal weighting of 0.5. 3. **Defuzzification:** Fuzzy outputs (membership values) were converted into a single 'crisp' value between 1 and 100 for each species, representing their food security, climate change, and biodiversity contribution potential. A score of 100 indicates the highest potential. The system used the defuzzification index values (Low=1, Medium=25, High=75, Very High=100) weighted by their accumulated membership values and averaged to obtain the final score. The fuzzy logic framework was applied to 54 major aquaculture species with data from Fishbase, SealifeBase, and additional sources. A jackknife analysis assessed the sensitivity of the system to input traits by sequentially removing each trait and recalculating FCB potential. This analysis identified traits with the largest impact on the system outputs.

The analysis revealed the following key findings: * **Trait Distribution:** 60% of identified traits were associated with food security, with considerable overlap with climate change and biodiversity traits. Two-thirds of food security traits also influenced climate change or biodiversity, indicating potential co-benefits. * **FCB Scores:** The mean FCB scores across all species were intermediate: food security (50), climate change (46), and biodiversity (53). Scores ranged from 1 to 100, with narrow to intermediate ranges for each index. * **Taxonomic Differences:** Significant differences in FCB potential existed between taxonomic groups. Non-fed species (algae and mollusks) generally scored higher than fed species (finfish and crustaceans). Algae and mollusks had significantly higher food and biodiversity scores than finfish and crustaceans. Algae also showed higher climate potential than mollusks. Crustaceans had significantly lower climate change scores than other groups. * **Species-Level Differences:** While taxonomic groups showed general trends, individual species within taxa exhibited substantial variation in FCB potential. Some finfish and crustacean species scored relatively high, highlighting the importance of species-specific assessments. * **Top-Performing Species:** Algae and mollusk species tended to rank highest across all FCB categories. Specific species like *Porphyra yezoensis*, *Porphyra tenera*, *Kappaphycus alvarezii*, and *Laminaria japonica* consistently demonstrated high potential. * **Low-Performing Species:** Crustacean and finfish species, including *Penaeus monodon* and *Sparus aurata*, scored lowest across all FCB categories. * **Case Study Comparison:** Japanese kelp (*Laminaria japonica*) outperformed Atlantic salmon (*Salmo salar*) and Pacific oyster (*Magallana gigas*) across all FCB indices. The high score of Japanese kelp suggests that its native relative, sugar kelp (*Saccharina latissima*), may hold similar potential. * **FCB Correlations:** Positive correlations were found between food security and climate change (tau = 0.441), food security and biodiversity (tau = 0.377), and climate change and biodiversity (tau = 0.283). This reflects the interconnectedness of these issues. * **Sensitivity Analysis:** The jackknife analysis revealed that food security was most sensitive to maximum size, VBGF K, absolute fecundity, macronutrients, nitrate, and phosphate range. Climate change was sensitive to nitrate range, phosphate range, salinity range, pO2 range, pH sensitivity, and trophic level. Biodiversity was most sensitive to VBGF K, absolute fecundity, latitudinal range, and geographic range.

The study's findings highlight the limitations of focusing solely on macronutrients and production in aquaculture. Although many species scored high for macronutrients, overall food security indices showed a narrow range and species typically associated with food security had lower than expected scores. This suggests that a singular focus on production might overshadow important FCB trade-offs and socio-economic factors influencing food security. High-yield production may not always align with local food security; for instance, most farmed fish are exported, not consumed locally. The study also emphasizes that traits beneficial for food production can sometimes have negative impacts on climate and biodiversity. For example, species with high fecundity and fast growth rates, traits advantageous for production, can also be successful invaders. The study suggests that manipulating traits related to trophic level and environmental range, which affect multiple FCB categories, can improve FCB potential through targeted breeding programs or changes in aquaculture practices.

This study provides a novel traits-based approach using fuzzy logic to assess the FCB potential of a broad range of aquaculture species. The findings reveal the importance of considering FCB trade-offs during species selection and highlight the superior performance of algae and mollusk species across multiple indices. Focusing on low trophic level species and implementing strategies like integrated multi-trophic aquaculture (IMTA) can help improve aquaculture's sustainability. Future research should integrate social-ecological factors to ensure that aquaculture development aligns with community needs and addresses existing socio-economic barriers. This includes further exploration of seaweed aquaculture and the potential of species like sugar kelp. Developing a comprehensive framework incorporating social-ecological traits is vital to guide sustainable aquaculture practices and achieve FCB goals.

The study acknowledges limitations related to data availability, particularly for non-fish species. While proxies were used where necessary, missing data could influence the results. The study also focused on biological and ecological traits and did not explicitly incorporate socio-economic factors, which are crucial for a holistic assessment. Future studies should incorporate social-ecological systems approaches to improve the evaluation of aquaculture’s contribution to FCB goals.