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Abstract Plants and mycorrhizal fungi form mutualistic relationships that affect how resources flow between organisms and within ecosystems. Common mycorrhizal networks (CMNs) could facilitate preferential transfer of carbon and limiting nutrients, but this remains difficult to predict. Do CMNs favour fungal resource acquisition at the expense of plant resource demands (a fungi‐centric view), or are they passive channels through which plants regulate resource fluxes (a plant‐centric view)?We used stable isotope tracers (¹³CO₂and¹⁵NH₃), plant traits, and mycorrhizal DNA to quantify above‐ and below‐ground carbon and nitrogen transfer between 18 plant species along a 520‐km latitudinal gradient in the Pacific Northwest, USA.Plant functional type and tissue stoichiometry were the most important predictors of interspecific resource transfer. Of ‘donor’ plants, 98% were¹³C‐enriched, but we detected transfer in only 2% of ‘receiver’ plants. However, all donors were¹⁵N‐enriched and we detected transfer in 81% of receivers. Nitrogen was preferentially transferred to annuals (0.26 ± 0.50 mg N per g leaf mass) compared with perennials (0.13 ± 0.30 mg N per g leaf mass). This corresponded with tissue stoichiometry differences.SynthesisOur findings suggest that plants and fungi that are located closer together in space and with stronger demand for resources over time are more likely to receive larger amounts of those limiting resources. Read the freePlain Language Summaryfor this article on the Journal blog. 

Soil microbiomes are heterogeneous, complex microbial communities. Metagenomic analysis is generating vast amounts of data, creating immense challenges in sequence assembly and analysis. Although advances in technology have resulted in the ability to easily collect large amounts of sequence data, soil samples containing thousands of unique taxa are often poorly characterized. These challenges reduce the usefulness of genome-resolved metagenomic (GRM) analysis seen in other fields of microbiology, such as the creation of high quality metagenomic assembled genomes and the adoption of genome scale modeling approaches. The absence of these resources restricts the scale of future research, limiting hypothesis generation and the predictive modeling of microbial communities. Creating publicly available databases of soil MAGs, similar to databases produced for other microbiomes, has the potential to transform scientific insights about soil microbiomes without requiring the computational resources and domain expertise for assembly and binning.