ArticleThe New phytologist2026
Atmospheric dust is a global nutrient source for plants via foliar uptake.
Article in The New phytologist, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Distinct Foliar Uptake Pathways for Phosphorus and Nano-Hydroxyapatite in Potato Revealed By Synchrotron μCT and ³³P Imaging.Plant, cell & environment · 2026Article
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6 authors.
Funding
Abstract
Atmospheric mineral dust is a critical nutrient supplier to marine ecosystems, but its role in terrestrial plant nutrition remains underexplored due to the assumption that nutrients are acquired solely from soils via roots. Here, we demonstrate that plants directly acquire nutrients from dust through leaves, revealing an unrecognized terrestrial uptake pathway. In a Mediterranean field study simulating dust events, dust application markedly increased plant macro and micronutrient concentrations, facilitated by the mildly acidic, organic-acid-rich leaf microenvironment that enhances dust dissolution and nutrient release. By integrating field observations with dust deposition estimates and soil nutrient data from different regions, we find that annual dust-derived inputs through leaves can account for up to 17% of soil-derived iron fluxes in the Western United States and up to 12% of phosphorus fluxes in the Eastern Amazon. During Mediterranean dust events, daily nutrient inputs can match or exceed soil-derived fluxes. Our findings suggest the major plant nutrition role of foliar dust uptake in nutrient-poor and dust-affected ecosystems. Such a foliar absorption pathway may become increasingly important as dust emissions and transport shift under future climate change and should be accounted for in vegetation, nutrients, and carbon-cycle models.
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