Strong modulation of nutrient distribution in <i>Alnus glutinosa</i> as a function of the actinorhizal symbiosis
Bibliographic record
Abstract
Micro- and macro-nutrient acquisition by plants and microorganisms is a cornerstone for their survival and has a direct impact on biogeochemical cycling. In this study, we investigated, in controlled conditions, how the availability of exogenous nitrate impacted nutrient acquisition and distribution in black alder (Alnus glutinosa (L.) Gaertn.) in the presence, or absence, of its nitrogen-fixing bacterial symbiont (Frankia sp.). Our findings show that alder physiology and distribution of nutrients between aerial and root tissues were strongly influenced by the presence of the symbiont. In both nodulated and non-nodulated alders, root allocation and total plant biomass were positively correlated, except when nodulated alders were subjected to low nitrate conditions (≤15 ppm). Alders receiving 45 ppm exogenous nitrate had a less developed actinorhizal symbiosis. These findings reflect the importance of root exploration in relation to plant dependence to exogenous nitrate. Nutrient composition of alder aerial tissues, in particular molybdenum, was significantly altered in the presence of Frankia. In the context of plant leaf-litter mutualism involving metals and N exchange, our findings of high Mo and P translocation to shoots of non-nodulated alders underscores how the state of the symbiosis in actinorhizal plants can influence the biogeochemical cycling of elements.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.000 | 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 source (direct Gemma or distilled Codex), 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".