Arbuscular mycorrhizal fungal genotype and nuclear organization as driving factors in host plant nutrient acquisition and stable carbon storage
Bibliographic record
Abstract
Societal Impact Statement It is crucial to develop strategies for reducing our continued excessive global increases in fertilizer applications and to offset CO 2 emissions. The pervasive underground hyphal networks of arbuscular mycorrhizal fungi (AMF) present an enticing bio‐stimulant and carbon sink. We inoculated Sudan‐grass plants with eight genotypically distinct strains of a model AMF species to determine if strain identity affects plant growth and carbon storage. We found that plant biomass, nutrient acquisition, and stable soil carbon inputs varied among strains, emphasizing the importance of AMF strain identity in the selection of AMF inoculants for optimizing crop yield and carbon storage. Summary Arbuscular mycorrhizal fungi (AMF) are obligate root symbionts of most plants that improve plant growth by transferring nutrients into plant roots through networks of soil hyphae. These hyphal networks represent a carbon sink in soil; thus, it has been suggested that these fungi can also boost atmospheric carbon storage, highlighting their potential role in managing greenhouse emissions. In this study, we aimed to determine whether certain AMF genotypes and nuclear organizations (homokaryons vs heterokaryons) are associated with higher rates of host plant yield and carbon storage. We compared Sudan‐grass ( Sorghum × drummondii ) AMF inoculation across eight strains of Rhizophagus irregularis : four homokaryotic and four heterokaryotic strains. Sudan‐grass was grown in a growth chamber, which included 13 C‐CO 2 pulse labeling to track plant carbon into AMF. AMF inoculation increased total and belowground biomass, as well as phosphorous, magnesium, and manganese uptake in the host. Heterokaryons led to greater belowground biomass, as well as less variable increases in shoot phosphorous. Mycorrhizal inputs to soil mineral‐associated organic carbon − a highly persistent carbon pool with slow turnover − were overall greater in heterokaryons than in homokaryons but varied significantly among strains. This indicates that the potential for carbon storage by mycorrhizal carbon inputs varies based on fungal genomic identity and nuclear organization. Overall, inoculation improved the yield of Sudan‐grass and resulted in significant inter‐strain variation in persistent carbon contributions to the soil. This work highlights the importance of considering genotype and nuclear identity in assessments of AMF as bio‐stimulants and drivers of carbon storage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".