Growth responses of Canada goldenrod ( <i>Solidago canadensis</i> L.) to increased nitrogen supply correlate with bioavailability of insoluble phosphorus source
Bibliographic record
Abstract
Abstract Anthropogenic nitrogen (N) inputs lead to the increase of phosphorus (P) demand for plants and plant species competition in a N enriched environment may hinge on its ability to utilize soil P sources. In soils, P mostly exists as insoluble phosphate compounds with three mineral elements: iron (Fe), aluminum (Al) or calcium (Ca), and it remains largely unknown whether invasive plant species are able to access such insoluble P sources and its interaction with N enrichment to gain competitive advantage. We determined the morphological traits, growth and nutrient status of an invasive plant Canada goldenrod ( Solidago canadensis L.) cultured in soluble phosphate KH 2 PO 4 (Ortho‐P), and insoluble inorganic phosphate AlPO 4 (Al–P), FePO 4 (Fe–P), Ca 5 (OH)(PO 4 ) 3 (Ca–P) at three N supply levels. Results showed that S. canadensis was able to selectively utilize P from Al–P but not from Fe–P or Ca–P by increasing root number and length under N additions. The increasing growth in S. canadensis was closely correlated with the increasing foliar P. Ability to utilize insoluble P sources under enriched N environment serves as a competitive advantage for S. canadensis in Al rich soils. Effective control of S. canadensis invasion may need to consider soil P management in the context of atmospheric N deposition as well.
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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 | 0.001 |
| 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 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".