Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Sodium constraints on megaherbivore communities in Africa

Nature Ecology & Evolution volume 10, pages 105–116 (2026)Cite this article

Subjects

Abstract

Sodium (Na) is an essential nutrient for animals, but not for most plants. Consequently, herbivores may confront a mismatch between forage availability and metabolic requirement. Recent work suggests that larger-bodied mammals may be particularly susceptible to Na deficits, yet it is unknown whether Na availability constrains the density or distribution of large herbivores at broad scales. Here we show that plant-Na availability varies >1,000-fold across sub-Saharan Africa and helps explain continent-scale patterns of large-herbivore abundance. We combined field data with machine-learning approaches to generate high-resolution maps of plant Na, which revealed multi-scale gradients arising from sea-salt deposition, hydrology, soil chemistry and plant traits. Faecal Na concentration was positively correlated with modelled dietary Na, supporting the prediction that variation in plant Na is a major determinant of herbivore Na intake. Incorporating plant-Na availability improved model predictions of large-herbivore population density, especially for megaherbivore species, which are depressed in very-low-Na regions (<100 mg kg−1), consistent with Na limitation. Our study offers an explanation for the scarcity of megaherbivores in parts of Central and West Africa, which has major ecological ramifications given the strong influence of large herbivores on ecosystem functioning and the profound human-induced changes to Na availability in Africa and beyond.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Spatial mapping of plant foliar Na concentration for C3 and C4 plant functional groups across sub-Saharan Africa.
Fig. 2: Herbivore Na intake as a function of plant Na gradients.
Fig. 3: Evidence that Na constrains megaherbivore densities.
Fig. 4: Na as a constraint on megaherbivore density across sub-Saharan Africa.

Similar content being viewed by others

Data availability

All data reported in this study are available via figshare at https://doi.org/10.6084/m9.figshare.25639080 (ref. 84). Source data are provided with this paper.

Code availability

All associated code generated in this study is available via figshare at https://doi.org/10.6084/m9.figshare.25639080 (ref. 84).

References

  1. Kaspari, M. & Powers, J. S. Biogeochemistry and geographical ecology: embracing all twenty-five elements required to build organisms. Am. Nat. 188, S62–S73 (2016).

    PubMed  Google Scholar 

  2. Robbins, C. Wildlife Feeding and Nutrition (Elsevier, 2012).

  3. Kaspari, M. The seventh macronutrient: how sodium shortfall ramifies through populations, food webs and ecosystems. Ecol. Lett. 23, 1153–1168 (2020).

    PubMed  Google Scholar 

  4. Suttle, N. F. Mineral Nutrition of Livestock (CABI, 2010).

  5. Duvall, E. S., Griffiths, B. M., Clauss, M. & Abraham, A. J. Allometry of sodium requirements and mineral lick use among herbivorous mammals. Oikos 2023, e10058 (2023).

    Google Scholar 

  6. Maathuis, F. J. M. Sodium in plants: perception, signalling, and regulation of sodium fluxes. J. Exp. Bot. 65, 849–858 (2014).

    PubMed  Google Scholar 

  7. Kronzucker, H. J., Coskun, D., Schulze, L. M., Wong, J. R. & Britto, D. T. Sodium as nutrient and toxicant. Plant Soil 369, 1–23 (2013).

    Google Scholar 

  8. Doughty, C. E., Wolf, A., Baraloto, C. & Malhi, Y. Interdependency of plants and animals in controlling the sodium balance of ecosystems and the impacts of global defaunation. Ecography 39, 204–212 (2016).

    Google Scholar 

  9. Bravo, A. & Harms, K. E. The biogeography of sodium in Neotropical figs (Moraceae). Biotropica 49, 18–22 (2017).

    Google Scholar 

  10. Borer, E. T. et al. More salt, please: global patterns, responses and impacts of foliar sodium in grasslands. Ecol. Lett. 22, 1136–1144 (2019).

    PubMed  Google Scholar 

  11. Abraham, A. J. et al. Anthropogenic supply of nutrients in a wildlife reserve may compromise conservation success. Biol. Conserv. 284, 110149 (2023).

    Google Scholar 

  12. Kaspari, M., Yanoviak, S. P., Dudley, R., Yuan, M. & Clay, N. A. Sodium shortage as a constraint on the carbon cycle in an inland tropical rainforest. Proc. Natl Acad. Sci. USA 106, 19405–19409 (2009).

    PubMed  PubMed Central  Google Scholar 

  13. Kaspari, M., Chang, C. & Weaver, J. Salted roads and sodium limitation in a northern forest ant community. Ecol. Entomol. 35, 543–548 (2010).

    Google Scholar 

  14. Snell-Rood, E. C. et al. Nutritional constraints on brain evolution: sodium and nitrogen limit brain size. Evolution 74, 2304–2319 (2020).

    PubMed  Google Scholar 

  15. Aumann, G. D. & Emlen, J. T. Relation of population density to sodium availability and sodium selection by microtine rodents. Nature 208, 198–199 (1965).

    PubMed  Google Scholar 

  16. Joyce, J. P. & Brunswick, L. C. F. Sodium supplementation of sheep and cattle fed lucerne. N. Z. J. Exp. Agric. 3, 299–304 (1975).

    Google Scholar 

  17. McNaughton, S. J. Mineral nutrition and spatial concentrations of African ungulates. Nature 334, 343–345 (1988).

    PubMed  Google Scholar 

  18. Weir, J. S. Spatial distribution of elephants in an African national park in relation to environmental sodium. Oikos 23, 1–13 (1972).

    Google Scholar 

  19. Sach, F., Dierenfeld, E. S., Langley-Evans, S. C., Watts, M. J. & Yon, L. African savanna elephants (Loxodonta africana) as an example of a herbivore making movement choices based on nutritional needs. Peer. J. 7, e6260 (2019).

    PubMed  PubMed Central  Google Scholar 

  20. Chamaillé-Jammes, S., Fritz, H. & Holdo, R. M. Spatial relationship between elephant and sodium concentration of water disappears as density increases in Hwange National Park, Zimbabwe. J. Trop. Ecol. 23, 725–728 (2007).

    Google Scholar 

  21. Abraham, A., Clauss, M., Bailey, M. & Duvall, E. Body mass scaling of sodium regulation in mammals. Acta Physiol. 241, e70090 (2025).

    Google Scholar 

  22. Griffiths, B. M., Luther, D. C. & Pollock, H. S. Mineral licks: an overlooked model system for species interactions. Biotropica 57, e70003 (2025).

    Google Scholar 

  23. Holdø, R. M., Dudley, J. P. & McDowell, L. R. Geophagy in the African elephant in relation to availability of dietary sodium. J. Mammal. 83, 652–664 (2002).

    Google Scholar 

  24. Santini, L., Benítez-López, A., Dormann, C. F. & Huijbregts, M. A. J. Population density estimates for terrestrial mammal species. Glob. Ecol. Biogeogr. 31, 978–994 (2022).

    Google Scholar 

  25. Olff, H., Ritchie, M. E. & Prins, H. H. T. Global environmental controls of diversity in large herbivores. Nature 415, 901–904 (2002).

    PubMed  Google Scholar 

  26. Pranzini, N., Maiorano, L., Cosentino, F., Thuiller, W. & Santini, L. The role of species interactions in shaping the geographic pattern of ungulate abundance across African savannah. Sci. Rep. 14, 19647 (2024).

    PubMed  PubMed Central  Google Scholar 

  27. Hempson, G. P., Archibald, S. & Bond, W. J. A continent-wide assessment of the form and intensity of large mammal herbivory in Africa. Science 350, 1056–1061 (2015).

    PubMed  Google Scholar 

  28. Coe, M. J., Cumming, D. H. & Phillipson, J. Biomass and production of large African herbivores in relation to rainfall and primary production. Oecologia 22, 341–354 (1976).

    PubMed  Google Scholar 

  29. Bell, R. H. V. in Ecology of Tropical Savannas (eds Huntley, B. J. & Walker, B. H.) 193–216 (Springer, 1982); https://doi.org/10.1007/978-3-642-68786-0_10

  30. East, R. Rainfall, soil nutrient status and biomass of large African savanna mammals. Afr. J. Ecol. 22, 245–270 (1984).

    Google Scholar 

  31. Fritz, H. & Duncan, P. On the carrying capacity for large ungulates of African savanna ecosystems. Proc. R. Soc. Lond. B 256, 77–82 (1997).

    Google Scholar 

  32. Pansu, J. et al. The generality of cryptic dietary niche differences in diverse large-herbivore assemblages. Proc. Natl Acad. Sci. USA 119, e2204400119 (2022).

    PubMed  PubMed Central  Google Scholar 

  33. Lynn, J. S., Fridley, J. D. & Vandvik, V. More than what they eat: uncoupled biophysical constraints underlie geographic patterns of herbivory. Ecography 2023, e06114 (2023).

    Google Scholar 

  34. Santiago-Rosario, L. Y., Harms, K. E., Elderd, B. D., Hart, P. B. & Dassanayake, M. No escape: the influence of substrate sodium on plant growth and tissue sodium responses. Ecol. Evol. 11, 14231–14249 (2021).

    PubMed  PubMed Central  Google Scholar 

  35. Abraham, A. J. et al. Sodium retention in large herbivores: physiological insights and zoogeochemical consequences. J. Exp. Zool. A 34, 664–676 (2025).

    Google Scholar 

  36. Hellgren, E. C. & Pitts, W. J. Sodium economy in white-tailed deer (Odocoileus virginianus). Physiol. Zool. https://doi.org/10.1086/515861 (1997).

  37. Weeks, H. P. & Kirkpatrick, C. M. Adaptations of white-tailed deer to naturally occurring sodium deficiencies. J. Wildl. Manag. 40, 610–625 (1976).

    Google Scholar 

  38. Christian, D. P. Effects of dietary sodium and potassium on mineral balance in captive meadow voles (Microtus pennsylvanicus). Can. J. Zool. 67, 168–177 (1989).

    Google Scholar 

  39. Clauss, M. et al. Mineral absorption in the black rhinoceros (Diceros bicornis) as compared with the domestic horse. J. Anim. Physiol. Anim. Nutr. 91, 193–204 (2007).

    Google Scholar 

  40. Clauss, M., Lang-Deuerling, S., Kienzle, E., Medici, E. P. & Hummel, J. Mineral absorption in tapirs (Tapirus spp.) as compared to the domestic horse. J. Anim. Physiol. Anim. Nutr. 93, 768–776 (2009).

    Google Scholar 

  41. Lindstedt, S. L. & Boyce, M. S. Seasonality, fasting endurance, and body size in mammals. Am. Nat. 125, 873–878 (1985).

    Google Scholar 

  42. Fa, J. E., Funk, S. M. & Nasi, R. Hunting Wildlife in the Tropics and Subtropics (Cambridge Univ. Press, 2022).

  43. Clauss, M., Steuer, P., Müller, D. W. H., Codron, D. & Hummel, J. Herbivory and body size: allometries of diet quality and gastrointestinal physiology, and implications for herbivore ecology and dinosaur gigantism. PLoS ONE 8, e68714 (2013).

    PubMed  PubMed Central  Google Scholar 

  44. Welti, E. A. R. et al. Salty, mild, and low plant biomass grasslands increase top-heaviness of invertebrate trophic pyramids. Glob. Ecol. Biogeogr. 29, 1474–1485 (2020).

    Google Scholar 

  45. Faurby, S. et al. PHYLACINE 1.2: the phylogenetic atlas of mammal macroecology. Ecology 99, 2626 (2018).

    PubMed  Google Scholar 

  46. Fritz, H. Low ungulate biomass in West African savannas: primary production or missing megaherbivores or large predator species?. Ecography 20, 417–421 (1997).

    Google Scholar 

  47. Churcher, C. S. A vacant niche? The curious distributions of African Perissodactyla. Trans. R. Soc. South Afr. 69, 1–8 (2014).

    Google Scholar 

  48. Morris, J. G. Assessment of sodium requirements of grazing beef cattle: a review. J. Anim. Sci. 50, 145–152 (1980).

    PubMed  Google Scholar 

  49. Brashares, J. S. et al. Bushmeat hunting, wildlife declines, and fish supply in West Africa. Science 306, 1180–1183 (2004).

    PubMed  Google Scholar 

  50. Cobb, A. & Cobb, S. Do zebra stripes influence thermoregulation?. J. Nat. Hist. 53, 863–879 (2019).

    Google Scholar 

  51. Kaspari, M. & Welti, E. A. R. Nutrient dilution and the future of herbivore populations. Trends Ecol. Evol. 39, 809–820 (2024).

    PubMed  Google Scholar 

  52. Clay, N. A., Lehrter, R. J. & Kaspari, M. Towards a geography of omnivory: omnivores increase carnivory when sodium is limiting. J. Anim. Ecol. 86, 1523–1531 (2017).

    PubMed  Google Scholar 

  53. Rothman, J. M., Van Soest, P. J. & Pell, A. N. Decaying wood is a sodium source for mountain gorillas. Biol. Lett. 2, 321–324 (2006).

    PubMed  PubMed Central  Google Scholar 

  54. Enquist, B. J., Abraham, A. J., Harfoot, M. B. J., Malhi, Y. & Doughty, C. E. The megabiota are disproportionately important for biosphere functioning. Nat. Commun. 11, 699 (2020).

    PubMed  PubMed Central  Google Scholar 

  55. Pringle, R. M. et al. Impacts of large herbivores on terrestrial ecosystems. Curr. Biol. 33, R584–R610 (2023).

    PubMed  Google Scholar 

  56. Bunney, K., Bond, W. J. & Henley, M. Seed dispersal kernel of the largest surviving megaherbivore—the African savanna elephant. Biotropica 49, 395–401 (2017).

    Google Scholar 

  57. Abraham, A. J. et al. Improved estimation of gut passage time considerably affects trait-based dispersal models. Funct. Ecol. 35, 860–869 (2021).

    Google Scholar 

  58. Kaushal, S. S. et al. The anthropogenic salt cycle. Nat. Rev. Earth Environ. 4, 770–784 (2023).

    PubMed  PubMed Central  Google Scholar 

  59. Moquet, J.-S. et al. Cl and Na fluxes in an Andean foreland basin of the Peruvian Amazon: an anthropogenic impact evidence. Aquat. Geochem. 20, 613–637 (2014).

    Google Scholar 

  60. Vet, R. et al. A global assessment of precipitation chemistry and deposition of sulfur, nitrogen, sea salt, base cations, organic acids, acidity and pH, and phosphorus. Atmos. Environ. 93, 3–100 (2014).

    Google Scholar 

  61. Osborne, C. P. et al. A global database of C4 photosynthesis in grasses. N. Phytol. 204, 441–446 (2014).

    Google Scholar 

  62. Griffith, D. M., Anderson, T. M. & Hamilton III, E. W. Ungulate grazing drives higher ramet turnover in sodium-adapted Serengeti grasses. J. Veg. Sci. 28, 815–823 (2017).

    Google Scholar 

  63. Baranga, D. Changes in chemical composition of food parts in the diet of Colobus monkeys. Ecology 64, 668–673 (1983).

    Google Scholar 

  64. Cooper, S. M., Owen-Smith, N. & Bryant, J. P. Foliage acceptability to browsing ruminants in relation to seasonal changes in the leaf chemistry of woody plants in a South African savanna. Oecologia 75, 336–342 (1988).

    PubMed  Google Scholar 

  65. Vogel, S. M. et al. Timing of dietary switching by savannah elephants in relation to crop consumption. Biol. Conserv. 249, 108703 (2020).

    Google Scholar 

  66. Chlingaryan, A., Sukkarieh, S. & Whelan, B. Machine learning approaches for crop yield prediction and nitrogen status estimation in precision agriculture: a review. Comput. Electron. Agric. 151, 61–69 (2018).

    Google Scholar 

  67. Hengl, T. et al. Soil nutrient maps of sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning. Nutr. Cycl. Agroecosyst. 109, 77–102 (2017).

    PubMed  PubMed Central  Google Scholar 

  68. Kuhn, M. caret: Classification and Regression Training. ascl:1505.003 (Astrophysics Source Code Library, 2015).

  69. Greenwell, B. et al. gbm: Generalized Boosted Regression Models. R version 2 (2019).

  70. Liaw, A. & Wiener, M. Classification and regression by randomForest. R. News 2, 18–22 (2002).

    Google Scholar 

  71. Venables, W. N. & Ripley, B. D. Modern Applied Statistics with S-PLUS. (Springer Science & Business Media, 2013).

  72. Karatzoglou, A., Smola, A., Hornik, K. & Zeileis, A. kernlab—an S4 package for kernel methods in R. J. Stat. Softw. 11, 1–20 (2004).

    Google Scholar 

  73. Ploton, P. et al. Spatial validation reveals poor predictive performance of large-scale ecological mapping models. Nat. Commun. 11, 4540 (2020).

    PubMed  PubMed Central  Google Scholar 

  74. Abraham, A. J. Large Mammals and the Zoogeochemistry of Terrestrial Nutrient Cycles. Dissertation, Northern Arizona Univ. (2021); https://www.proquest.com/openview/bad9b84990a7d22c60dac15c0d978473/1?pq-origsite=gscholar&cbl=18750&diss=y

  75. Wood, S. N. Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. J. R. Stat. Soc. Ser. B 73, 3–36 (2011).

    Google Scholar 

  76. Glazier, D. S. Biological scaling analyses are more than statistical line fitting. J. Exp. Biol. 224, jeb241059 (2021).

    PubMed  Google Scholar 

  77. White, F. The Vegetation of Africa; a Descriptive Memoir to Accompany the UNESCO/AETFAT/UNSO Vegetation Map of Africa (UNESCO, 1983); https://unesdoc.unesco.org/ark:/48223/pf0000058054

  78. Wood, S. N., Bravington, M. V. & Hedley, S. L. Soap film smoothing. J. R. Stat. Soc. Ser. B 70, 931–955 (2008).

    Google Scholar 

  79. Pedersen, E. J., Miller, D. L., Simpson, G. L. & Ross, N. Hierarchical generalized additive models in ecology: an introduction with mgcv. Peer J. 7, e6876 (2019).

    PubMed  PubMed Central  Google Scholar 

  80. Marra, G. & Wood, S. N. Practical variable selection for generalized additive models. Comput. Stat. Data Anal. 55, 2372–2387 (2011).

    Google Scholar 

  81. Anderson, D. R. & Burnham, K. P. Avoiding pitfalls when using information-theoretic methods. J. Wildl. Manag. 66, 912–918 (2002).

    Google Scholar 

  82. Simpson, G. L. & Singmann, H. gratia: Graceful ‘ggplot’-Based Graphics and Other Functions for GAMs Fitted Using 'mgcv'. (2018).

  83. Roberts, D. R. et al. Cross-validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure. Ecography 40, 913–929 (2017).

    Google Scholar 

  84. Abraham, A. J. et al. Sodium constraints on megaherbivore communities in Africa. figshare https://doi.org/10.6084/m9.figshare.25639080 (2025).

Download references

Acknowledgements

We acknowledge many funding bodies that have facilitated this project, including NASA awards 16-HW16_2-0025 and 18-SLSCVC18-0032 (C.E.D. and A.J.A.), a Google Earth Engine research award (C.E.D. and A.J.A.), Horizon Europe Marie Skłodowska-Curie Actions grant agreement number 101062339 (A.J.A.), the Royal Society Newton International Fund and the Independent Research Fund Denmark’s (Danmarks Frie Forskningsfond (DFF)) Inge Lehmann programme under grant agreement number 1131-00006B (E.L.R.), the Carlsberg Foundation Semper Ardens project MegaPast2Future grant CF16-0005 (J.-C.S.), the Center for Ecological Dynamics in a Novel Biosphere (ECONOVO) funded by Danish National Research Foundation (grant DNRF173) and VILLUM Investigator project ‘Biodiversity Dynamics in a Changing World’ funded by VILLUM FONDEN grant 16549 (J.-C.S.), AfricanBioServices project funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement 641918 (J.G.C.H. and M.P.V.) and the US National Science Foundation IOS-1656527, DEB-2225088 (R.M.P.). We thank the management and staff of all wildlife reserves within which research was conducted. In particular, we thank the Tswalu Foundation for their financial support and facilitation of this project. We also thank K. Parr, E. Lundgren, O. Baines and members of the International Network to study Deposition and Atmospheric composition in Africa (INDAAF) for helpful comments during the preparation of this paper, J. Lloyd and K. Rode for sharing of data and D. Leese and S. Abraham for their help in collecting faecal samples.

Author information

Authors and Affiliations

  1. School of Informatics, Computing and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA

    Andrew J. Abraham, Tomos Prys-Jones, Chase Ridenour & Christopher E. Doughty

  2. Center for Ecological Dynamics in a Novel Biosphere (ECONOVO), Department of Biology, Aarhus University, Aarhus, Denmark

    Andrew J. Abraham, Elizabeth le Roux, Celesté Maré & Jens-Christian Svenning

  3. Centre for African Ecology, School of Animal, Plant and Environmental Sciences, University of the Witwatersrand, Johannesburg, South Africa

    Gareth P. Hempson & Norman Owen-Smith

  4. Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, UK

    Gareth P. Hempson & J. Grant C. Hopcraft

  5. Mammal Research Institute, Faculty of Natural and Agricultural Sciences, University of Pretoria, Pretoria, South Africa

    Elizabeth le Roux & Andrea B. Webster

  6. School of Biosciences, University of Sheffield, Sheffield, UK

    Lyla L. Taylor

  7. Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA

    Ethan S. Duvall

  8. Independent researcher, Bath, UK

    John Coppock

  9. Soil Sciences Laboratory, Department of Plant and Soil Science, University of Pretoria, Pretoria, South Africa

    Pieter de Jager

  10. Rangeland Resources and Systems Research Unit, USDA-Agricultural Research Service, Fort Collins, CO, USA

    David Augustine

  11. Biology Department, Vancouver Island University, Nanaimo, British Columbia, Canada

    Colin A. Chapman

  12. Wilson Center, Washington DC, USA

    Colin A. Chapman

  13. Shaanxi Key Laboratory for Animal Conservation, Northwest University, Xi’an, China

    Colin A. Chapman

  14. School of Life Sciences, University of KwaZulu-Natal, Pietermaritzburg, South Africa

    Colin A. Chapman

  15. Division of Anthropology and Environmental Studies Program, California State University, Fullerton, Fullerton, CA, USA

    Peter J. Fashing & Nga Nguyen

  16. Centre for Ecological and Evolutionary Synthesis, University of Oslo, Oslo, Norway

    Peter J. Fashing & Nga Nguyen

  17. Vizzuality, Madrid, Spain

    Michael B. J. Harfoot

  18. Odum School of Ecology, University of Georgia, Athens, GA, USA

    Ricardo M. Holdo

  19. Department of Sociology and Anthropology, Fordham University, New York, NY, USA

    Caley Johnson

  20. Wildlife Ecology and Conservation Group, Wageningen University and Research, Wageningen, The Netherlands

    Frank van Langevelde

  21. Environmental Change Institute, School of Geography and the Environment, University of Oxford, Oxford, UK

    Yadvinder Malhi & Eleanor R. Thomson

  22. Division of Energy, Environment and Socitey, University of Dundee, Dundee, UK

    Alexandra Morel

  23. Department of Biology, Wake Forest University, Winston-Salem, NC, USA

    Arjun B. Potter

  24. Department of Animal Sciences, Wageningen University and Research, Wageningen, The Netherlands

    Herbert H. T. Prins

  25. Department of Anthropology, Hunter College of the City University of New York, New York, NY, USA

    Jessica M. Rothman

  26. New York Consortium in Evolutionary Primatology, New York, NY, USA

    Jessica M. Rothman & Larissa Swedell

  27. Department of Conservation, Uganda Wildlife Authority, Kampala, Uganda

    Jessica M. Rothman

  28. Department of Anthropology, Queens College of the City University of New York, New York, NY, USA

    Larissa Swedell

  29. Plant Ecology and Nature Conservation Group, Wageningen University, Wageningen, The Netherlands

    Fons van der Plas

  30. Institute of Environmental Sciences, Leiden University, Leiden, The Netherlands

    Michiel P. Veldhuis

  31. Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA

    Robert M. Pringle

  32. Clinic for Zoo Animals, Exotic Pets and Wildlife, Vetsuisse Faculty, University of Zurich, Zurich, Switzerland

    Marcus Clauss

Authors
  1. Andrew J. Abraham
    View author publications

    Search author on:PubMed Google Scholar

  2. Gareth P. Hempson
    View author publications

    Search author on:PubMed Google Scholar

  3. Elizabeth le Roux
    View author publications

    Search author on:PubMed Google Scholar

  4. Celesté Maré
    View author publications

    Search author on:PubMed Google Scholar

  5. Lyla L. Taylor
    View author publications

    Search author on:PubMed Google Scholar

  6. Andrea B. Webster
    View author publications

    Search author on:PubMed Google Scholar

  7. Ethan S. Duvall
    View author publications

    Search author on:PubMed Google Scholar

  8. Tomos Prys-Jones
    View author publications

    Search author on:PubMed Google Scholar

  9. John Coppock
    View author publications

    Search author on:PubMed Google Scholar

  10. Chase Ridenour
    View author publications

    Search author on:PubMed Google Scholar

  11. Pieter de Jager
    View author publications

    Search author on:PubMed Google Scholar

  12. David Augustine
    View author publications

    Search author on:PubMed Google Scholar

  13. Colin A. Chapman
    View author publications

    Search author on:PubMed Google Scholar

  14. Peter J. Fashing
    View author publications

    Search author on:PubMed Google Scholar

  15. Michael B. J. Harfoot
    View author publications

    Search author on:PubMed Google Scholar

  16. Ricardo M. Holdo
    View author publications

    Search author on:PubMed Google Scholar

  17. J. Grant C. Hopcraft
    View author publications

    Search author on:PubMed Google Scholar

  18. Caley Johnson
    View author publications

    Search author on:PubMed Google Scholar

  19. Frank van Langevelde
    View author publications

    Search author on:PubMed Google Scholar

  20. Yadvinder Malhi
    View author publications

    Search author on:PubMed Google Scholar

  21. Alexandra Morel
    View author publications

    Search author on:PubMed Google Scholar

  22. Nga Nguyen
    View author publications

    Search author on:PubMed Google Scholar

  23. Norman Owen-Smith
    View author publications

    Search author on:PubMed Google Scholar

  24. Arjun B. Potter
    View author publications

    Search author on:PubMed Google Scholar

  25. Herbert H. T. Prins
    View author publications

    Search author on:PubMed Google Scholar

  26. Jessica M. Rothman
    View author publications

    Search author on:PubMed Google Scholar

  27. Larissa Swedell
    View author publications

    Search author on:PubMed Google Scholar

  28. Jens-Christian Svenning
    View author publications

    Search author on:PubMed Google Scholar

  29. Eleanor R. Thomson
    View author publications

    Search author on:PubMed Google Scholar

  30. Fons van der Plas
    View author publications

    Search author on:PubMed Google Scholar

  31. Michiel P. Veldhuis
    View author publications

    Search author on:PubMed Google Scholar

  32. Robert M. Pringle
    View author publications

    Search author on:PubMed Google Scholar

  33. Marcus Clauss
    View author publications

    Search author on:PubMed Google Scholar

  34. Christopher E. Doughty
    View author publications

    Search author on:PubMed Google Scholar

Contributions

A.J.A., C.E.D., T.P.-J., E.R.T. and M.B.J.H. developed and framed the research question. A.J.A., J.C., T.P.-J., A.B.W. and C.D. conducted fieldwork specifically for this project. A.B.W. and P.D.J. conducted laboratory analysis. A.J.A., G.P.H. and L.L.T. collated datasets required for this study. E.L.R., D.A., C.A.C., P.J.F., R.M.H., G.P.H., C.J., F.V.L., Y.M., A.M., N.N., N.O.-S., A.B.P., R.M.P., H.H.T.P., J.M.R., L.S., F.V.D.P., M.P.V. and J.-C.S. contributed data. A.J.A., C.M., M.C., E.S.D., T.P.-J. and C.R. performed statistical analysis. A.J.A. wrote the first draft of the paper, and all authors contributed substantially to revisions.

Corresponding author

Correspondence to Andrew J. Abraham.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Ecology & Evolution thanks Julia Monk, Matteo Rizzuto, Ellen Welti and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Plant sodium (Na) concentrations across sub-Saharan Africa.

(A) Relationship between median community foliar Na concentration and aerosol deposition (see Fig. S3b). Increased opacity of points represents an increased number of measurements recorded within the foliar community. Trend lines for C3 and C4 plant functional groups represent ordinary least squares fits weighted by the log10 + 1 number of measurements recorded within each community (cf. Figure 1). Error bars represent Standard Error. Median measured community foliar Na concentration for C3 plants (B) and C4 grasses (C) located across sub-Saharan Africa. The cluster of grass points in the Serengeti-Mara ecosystem is illustrated at higher spatial resolution for clarity. Map elements created with Natural Earth (https://www.naturalearthdata.com).

Source Data

Extended Data Fig. 2 Performance of machine learning models used to predict plant sodium (Na) concentrations across sub-Saharan Africa.

Root mean squared error (RMSE) and R2 model performance metrics of the buffered leave-one-out cross validation (BLOOCV) for (a, b) median and (c, d) 95th percentile foliar Na concentration prediction models. The black circles above the first graph represents the average number of training points removed from within each buffer distance. CUBIST = cubist model; GBM = Gradient boosted model; NNET = neural network model; RF = random forest model; SPATIAL = kernel smoothing model; SSA = sea salt aerosol model; SVM = support vector machine model. e) Spatial mapping of distance to the nearest training point across sub-Saharan Africa. Contour lines represent 300 km intervals. Map elements created with Natural Earth (https://www.naturalearthdata.com).

Source Data

Extended Data Fig. 3 Spatial mapping of 95th percentile plant foliar sodium (Na) concentration for (a) C3 and (b) C4 plant functional groups at a 0.1° resolution across sub-Saharan Africa.

This is representative of plant Na availability to herbivores under a selective foraging scenario. To better visualise geographic patterns, concentrations have been plotted on a log10 scale. Silhouettes from PhyloPic under a Creative Commons license CC0 1.0: plant, T. Michael Keesey; grass, Mason McNair; map elements created with Natural Earth (https://www.naturalearthdata.com).

Source Data

Extended Data Fig. 4 Drivers of foliar sodium (Na) concentration across sub-Saharan Africa.

Partial dependence plots for predicting foliar median (unselective foraging scenario) and 95th percentile (selective foraging scenario) sodium (Na) concentration using the ensemble model. The relationship between foliar Na concentration (yhat) and each variable is highlighted by the red line. Note: the scale for aridity is non-intuitive, with lower scores reflecting more arid environments.

Source Data

Extended Data Fig. 5 Herbivore sodium (Na) intake as a function of plant Na gradients.

Relationship between modelled dietary forage Na concentration and field-measured herbivore faecal Na concentration using the unselective foraging scenario. Points and vertical error bars represent the mean ± 1 SD faecal Na concentration per genus per protected area. The total number of independent points is n = 111 from 20 genera across 20 protected areas. Note that axes are on log10 scales to emphasise attention on low-values that may be indicative of Na limitation. The black line represents the fit of a linear mixed effects model with species included as a random effect. The marginal R2 (fixed effects) denotes the proportion of variance explained by dietary Na availability. Analogous results for the 95th percentile (selective) scenario are in Fig. 2a.

Source Data

Extended Data Fig. 6 Drivers of large-herbivore density across sub-Saharan Africa.

Partial dependence plots for covariates in the best generalised additive mixed model (GAMM) for estimating large-herbivore density using all available observations. Plots indicate how large-herbivore density is predicted to change across the range of each covariate. Error bars represent 95% confidence intervals. For interaction plots, blue colours indicate density decrease, and red colours density increase. Map elements created with Natural Earth (https://www.naturalearthdata.com).

Source Data

Extended Data Fig. 7 Drivers of megaherbivore density across sub-Saharan Africa.

Partial dependence plots for covariates in the best generalised additive mixed model (GAMM) for estimating large-herbivore density using megaherbivore observations only. Plots indicate how megaherbivore density is predicted to change across the range of each covariate. Error bars represent 95% confidence intervals. For interaction plots, blue colours indicate density decrease, and red colours density increase. Map elements created with Natural Earth (https://www.naturalearthdata.com).

Source Data

Supplementary information

Supplementary Information

Supplementary Text 1–3, Supplementary Tables 1–8 and Supplementary Figs. 1–10.

Reporting Summary

Peer Review File

Source data

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Abraham, A.J., Hempson, G.P., le Roux, E. et al. Sodium constraints on megaherbivore communities in Africa. Nat Ecol Evol 10, 105–116 (2026). https://doi.org/10.1038/s41559-025-02917-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41559-025-02917-y

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing