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Global plant diversity as a reservoir of micronutrients for humanity

Abstract

With more than two billion people suffering from malnutrition and diets homogenizing globally, it is vital to identify and conserve nutrient-rich species that may contribute to improving food security and diversifying diets. Of the approximately 390,000 vascular plant species known to science, thousands have been reported to be edible, yet their nutritional content remains poorly characterized. Here we use phylogenetic information to identify plants with the greatest potential to support strategies alleviating B-vitamin deficiencies. We predict the B-vitamin profiles of >6,400 edible plants lacking nutritional data and identify 1,044 species as promising key sources of B vitamins. Several of these source species should become conservation priorities, as 63 (6%) are threatened in the wild and 272 (26%) are absent from seed banks. Moreover, many of these conservation-priority source species overlap with hotspots of malnutrition, highlighting the need for safeguarding strategies to ensure that edible plant diversity remains a reservoir of nutrition for future generations, particularly in countries needing it most. Although by no means a silver bullet to tackling malnutrition, conserving a diverse portfolio of edible plants, unravelling their nutritional potentials, and promoting their sustainable use are essential strategies to enhance global nutritional resilience.

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Fig. 1: Phylogenetic trees of terrestrial angiosperm edible plant species with their corresponding B-vitamin profiles.
Fig. 2: In situ threat and ex situ conservation status of all documented terrestrial edible angiosperm species and predicted B-vitamin source species.
Fig. 3: Percentages of B-vitamin source species that are globally threatened in situ and not conserved ex situ in 244 countries and island states.

Data availability

All data used were accessed from publicly available databases and are indicated in the Methods. B-vitamin predictions are available in Supplementary Data 1 and 2. Species predicted to be B-vitamin sources under the conservative and ‘best-case’ scenarios are listed in Supplementary Data 3, with the names of the countries in which each consensus source species is found. Supplementary Data 4 contains, for each country, the number of source species, percentages of source species that are threatened in situ and not conserved ex situ, and the prevalence of each B-vitamin deficiency. A list of the nutritionally known edible species used is available in Supplementary Table 8.

Code availability

R scripts for testing for phylogenetic signal, and performing the predictions for the nutritionally known and unknown species are available in Supplementary Software 14.

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Acknowledgements

A.C.-J. was funded by the Basil Furneaux Memorial Fund, Imperial College London, and the Natural Environment Research Council (NE/S007415/1). B.V. received funding from the Wellcome Trust Our Plant, Our Health programme (Grant number: 106864MA). S.P. received funding from Royal Botanic Gardens, Kew pilot study fund (reference: 11492-100). We thank M. Soto Gomez, the Gill and Graystock lab group (Imperial College London), and the Science Directorate (Royal Botanic Gardens, Kew) for feedback on project ideas; M. Bidartondo for comments on this manuscript; N. Black, R. Govaerts, I. Ondo and R. Turner for help with accessing the World Checklist of Vascular Plants and Useful Plants data; D. Satori and T. Cossu for help with accessing conservation data; F. Fletcher for help with assembling the nutritional data; K. Kam for help with code; and P. Jones for proofreading.

Author information

Authors and Affiliations

Authors

Contributions

S.P. conceived the project. A.C.-J. and S.P. designed the study. A.C.-J. and J.B. collected the nutritional data. M.D. and T.U. compiled and provided the list of edible plant species. D.C. and B.V. developed and provided the code for the nutrient predictions. S.P. provided the data on plant distributions. A.C.-J. performed analyses with guidance from S.P., F.F., J.H., M.-J.R.H. and R.D. A.C.-J. wrote the manuscript with guidance from S.P. All authors provided feedback on the manuscript and gave authorization for publication.

Corresponding authors

Correspondence to Aoife Cantwell-Jones or Samuel Pironon.

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No competing interests.

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Nature Plants thanks Christine Foyer, Nora Castañeda, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Predicted versus observed values (and their relationships) for B vitamins in nutritionally known species.

The different colours represent the different B vitamins (see legend). The coloured lines are the relationships between predicted and observed values (using generalised least squares models). The dashed line represents a relationship where the predicted and observed values are equal. Circles denote observed nutritionally known values which did not lie within the 95% confidence intervals of their predicted values. Predicted and observed values for each B vitamin were standardised prior to plotting.

Extended Data Fig. 2 Summary of the method used to estimate the B-vitamin profiles of nutritionally unknown species.

1) The branches of the phylogenetic tree are rescaled (often resulting in shortening internal branches relative to terminal branches, as in the second tree), so that the B-vitamin profiles of the nutritionally known species match the distribution expected under a Brownian-motion model. The parameter λ is used for this rescaling and represents the strength of phylogenetic signal for a given B vitamin, with values close to 1 suggesting strong signal64. The parameter σ2 is the estimated variance of the Brownian-motion process for a given nutrient. 2) The B-vitamin concentrations of the most recent common ancestors are estimated using the fastAnc function from “phytools”65, data for nutritionally known species, and the rescaled phylogeny. 3) The B-vitamin concentrations for nutritionally unknown edible species (here represented by “?”) are approximated as the values of the most recent common ancestors between the nutritionally unknown species and its most closely related nutritionally known species. The standard deviation (SD) of the prediction is calculated as the product of the variance of the Brownian-motion (σ2) and the branch length of the nutritionally unknown species to its most recent common ancestor with a nutritionally known species (t). CI refers to confidence intervals.

Extended Data Fig. 3 Prevalence of inadequate B-vitamin intake (%) and counts of B-vitamin-source species per country.

Inadequate B-vitamin intake is represented by the Prevalence of Inadequate Micronutrient Intake Index1. Light grey represents missing inadequate-intake data; blue, low inadequate intake and many source species; red, high inadequate intake and few source species; and brown, high inadequate intake and many source species. Brown countries are those that could benefit most, nutritionally, from their edible plant diversity. The axes labels on the legend in Extended Data Fig. 3a apply to the other subplots. The numerical ranges for each colour (indicated in the legends) were generated using Fisher natural breaks classification method76 and differ for each subplot for improved visualisation.

Extended Data Fig. 4 Prevalence of inadequate B-vitamin intake (%) and percentages of threatened B-vitamin-source species per country.

Inadequate B-vitamin intake is represented by the Prevalence of Inadequate Micronutrient Intake Index1. Light grey represents missing inadequate-intake data or no B-vitamin-source species; blue, low inadequate intake and a low percentage of threatened source species; dark grey, low inadequate intake and a high percentage of threatened source species; red, high inadequate intake and a low percentage of threatened source species; and black, high inadequate intake and a high percentage of threatened source species. Black countries are those that should prioritise most in-situ edible plant conservation. “Threatened species” are those that are possibly threatened, threatened or extinct in the wild, according to the Botanic Gardens Conservation International ThreatSearch database32. The axes labels on the legend in Extended Data Fig. 4a apply to the other subplots. The numerical ranges for each colour (indicated in the legends) were generated using Fisher natural breaks classification method76 and differ for each subplot for improved visualisation.

Extended Data Fig. 5 Prevalence of inadequate B-vitamin intake (%) and percentages of B-vitamin-source species that are not conserved ex situ, per country.

Inadequate B-vitamin intake is represented by the Prevalence of Inadequate Micronutrient Intake Index1. Light grey represents missing inadequate-intake data or no B-vitamin-source species; blue, low inadequate intake and a low percentage of source species not conserved ex situ; dark grey, low inadequate intake and a high percentage of source species not conserved ex situ; red, high inadequate intake and a low percentage of source species not conserved ex situ; and black, high inadequate intake and high percentage of source species not conserved ex situ. Black countries are those that should prioritise most ex-situ edible plant conservation. Species “not conserved ex situ” refers to those absent from Genesys34 and the Millennium Seed Bank Partnership databases33. The axes labels on the legend in Extended Data Fig. 5a apply to the other subplots. The numerical ranges for each colour (indicated in the legends) were generated using Fisher natural breaks classification method76 and differ for each subplot for improved visualisation.

Supplementary information

Supplementary Information

Supplementary Tables 1–10 and Methods.

Reporting Summary

Supplementary Data 1

Predicted values for nutritionally known species (using jackknifing) for thiamine, riboflavin, niacin, pantothenic acid and folate, following the approach of Vaitla et al.19.

Supplementary Data 2

Edible plant predictions (nutritionally unknown species) for thiamine, riboflavin, niacin, pantothenic acid and folate, following the approach of Vaitla et al.19.

Supplementary Data 3

Consensus and best-case B-vitamin source species. These plants were either predicted to be B-vitamin sources by both prediction methods or at least one prediction method, respectively. The countries in which the consensus source species are found are also given.

Supplementary Data 4

For each country, the number of source species, the percentages of source species that are threatened in situ and not conserved ex situ, and the prevalence of deficiency of thiamine, riboflavin, niacin and folate.

Supplementary Software 1

R script for measuring phylogenetic signal of B vitamins in nutritionally known species.

Supplementary Software 2

R script for predicting the B-vitamin concentrations for nutritionally unknown species, following the method of Vaitla et al.19.

Supplementary Software 3

R script for validating the prediction method of Vaitla et al.19 by predicting the B-vitamin concentrations of nutritionally known species.

Supplementary Software 4

R script for predicting B-vitamin source species using the ‘hot-node’ approach.

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Cantwell-Jones, A., Ball, J., Collar, D. et al. Global plant diversity as a reservoir of micronutrients for humanity. Nat. Plants 8, 225–232 (2022). https://doi.org/10.1038/s41477-022-01100-6

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