Abstract
Wild fish harvests from freshwaters and oceans per person on Earth have been stagnating for decades due to increased food demand from a burgeoning global human population, raising the stakes for maximizing the nutritional benefits from limited fish stocks. Here we adopt an allocation optimization approach using biogeographic and nutrient data for the world’s fishes to identify ideal portfolios of species for consumption in every country. We find that, across nations, biodiversity increases opportunities to fulfil multiple nutritional requirements with less fish biomass. This advantage emerges through complementarity among species; portfolios of complementary species provide >60% more nutrients than the same biomass of the most nutrient-rich species. Moreover, biodiverse fisheries enable harvest allocation towards species with traits enhancing fishery resilience (for example, small size, low trophic position) and offer greater redundancy, whereby a wider range of comparably nutritious species is available. Our analysis underscores that conserving fish biodiversity can improve nutrition and fishery resilience while reducing harvest pressure on already-stressed aquatic ecosystems.
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Data availability
Data for replicating the analysis and results are available via Figshare at https://doi.org/10.6084/m9.figshare.24615465 (ref. 49). The Aquatic Resource Trade in Species (ARTIS) database is accessible at https://artisdata.weebly.com/ (ref. 27).
Code availability
Code supporting the results is available via Figshare at https://doi.org/10.6084/m9.figshare.24615465 (ref. 49).
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Acknowledgements
We thank C. Bowser, E. Duvall, M. Miranda, F. Pacheco, M. Valdverde and L. Zarri for providing comments that improved the manuscript. We also thank the many researchers that analysed fish nutrient content and developed predictive models for unmeasured species. This project is partially supported by Schmidt Sciences programmes, through an Eric & Wendy Schmidt AI in Science Postdoctoral Fellowship (S.A.H.) and an AI2050 Senior Fellowship (C.G.); a Cornell Presidential Postdoctoral Fellowship (S.A.H.); the National Science Foundation and the National Institute of Food and Agriculture (NSF and USDA/NIFA) no. 2023-67021-39829 (C.G.); the Air Force Office of Scientific Research no. FA9550-23-1-0322 (C.G.) and no. FA9550-23-1-0569 (DURIP; CG); and a David and Lucile Packard Fellowship for Science and Engineering (P.B.M.).
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S.A.H. conceived the study with substantial input from F.W.S. and P.B.M; all authors contributed to refining the study design; S.A.H. and F.W.S. developed the methodology and analysis; S.A.H. wrote the first draft with support from P.B.M.; all authors contributed to reviewing and editing.
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Extended data
Extended Data Fig. 1 Variation in nutrient content across all food fish species (grey), and for specific countries (green; first column: Iceland; second column: Kiribati; third column: Kenya), as depicted by the first three principal components using all nutrient content values (for example, protein, iron, zinc, calcium, vitamin A and omega-3s [EPA+DHA]).
Complementary species (orange) are the species included within optimal portfolios, while the best species (purple) is the single species that minimizes the biomass needed to support all RDAs. When a single best species is also included in an optimal portfolio, it is orange and outlined in black. More biodiverse countries are typically represented by a wider variation in nutritional trait space. Species included in the optimal portfolio are drawn from the edges of nutritional space, but do not overlap.
Extended Data Fig. 2 The species richness of an optimal portfolio (SOpt) increases as more RDAs are considered but never exceeds four species.
Each point represents a country (n=291) colored by it’s biodiversity endowment (S). Increasing the number of RDAs considered also leads to an increase in the minimum portion size needed (Pmin), but more speciose portfolios are associated with lower Pmin. Box plots display the median (center line), interquartile range (box) and whiskers (minimum and maximum values within 1.5 × IQR).
Extended Data Fig. 3 The wider aggregate nutrient trait content variation in more biodiverse countries increased the potential to assemble optimal species portfolios or select single best species with nutritionally extreme values.
(A) Species from countries with higher biodiversity exhibit more variation in nutrient content, measured as the convex hull volume considering six key nutrients derived from fish. (B) The mean nutrient trait distance of all species within a country tends to be lower than the mean nutrient trait distance of species in optimal portfolios (the black line represents the 1:1 line, with points above representing countries where the mean nutrient trait distance of optimal species is larger than of all species within that respective country). (C) The mean nutrient trait distance of all species within a country tends to be lower than the mean nutrient trait distance of single best species (the black line represents the 1:1 line, with points above representing countries where the mean nutrient trait distance of the single best species is larger than of all species within that respective country). Each point corresponds to a country (n=290).
Extended Data Fig. 4 Randomly assembled portfolios from countries with high biodiversity required less biomass to meet RDAs, but differences with portfolios based on complementarity and selection were exceptionally large (n=290).
Random portfolios were assembled by drawing a random sample of the same number of species represented in the optimal portfolio from each country (see methods). For full statistical results see Table S1. Panel B is a close-up of panel A.
Extended Data Fig. 5 Countries well-endowed with biodiversity sustain nutritionally complete diets with less biomass regardless of (A) %RDA thresholds or (B) number of RDAs considered.
The biodiversity effect (that is, estimated effect of S on on Pmin) does not vary based on (C) thresholds but (D) becomes stronger when more RDAs are considered. The biodiversity effect was obtained by using a generalized linear model and extracting the estimates and 95% confidence intervals.
Extended Data Fig. 6 The species composition of optimal portfolios depends on the number and type of nutrient RDAs are considered.
Each point represents a country (n=290) colored by the number of species within an optimal portfolio as indicated in the legend in (A), with lines connecting the same country. Points are jittered for interpretability. Dissimilarity, turnover and nestedness are measured as the pairwise differences between each successive number of RDAs for each country, with 0 indicating that there are no differences in optimal species composition and 1 indicating complete compositional turnover when comparing successive number of RDAs. For example, for the vast majority of countries the species composition of optimal portfolios that meet 2 RDAs is completely different than the species that are optimal to meet one RDA. When increasing from one to three RDAs, compositional changes are primarily driven (B) turnover, which represents changes in species composition driven by replacement of some species by others that were not previously included. When increasing from four to six RDAs, compositional changes are represented by a mixture of turnover and (C) nestedness, the latter representing changes in species composition driven by gains or losses of species.
Extended Data Fig. 7 Biodiversity gradient with random species draws from a global pool retains the same relationship between species richness and the minimum amount of fish biomass to meet RDAs based on complementarity and selection.
To build this random biodiversity gradient we sampled the global pool of species without replacement from 1 to 756 species, which is the species richness range for the number of food fishes available across nations. For every level of species richness, we performed this randomization 30 times for all 290 countries for a total of 8,700 random assemblages.
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Heilpern, S.A., Simon, F.W., Sethi, S.A. et al. Leveraging biodiversity to maximize nutrition and resilience of global fisheries. Nat Sustain (2025). https://doi.org/10.1038/s41893-025-01577-x
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DOI: https://doi.org/10.1038/s41893-025-01577-x
