Shade does not decrease nitrogen fixation in the boreal shrub <i>Shepherdia canadensis</i>
Bibliographic record
Abstract
High-latitude environments are characterized by harsh abiotic conditions that limit nitrogen availability to plants. However, even though these environments are nitrogen-limited, nitrogen-fixing plants are less prevalent at higher latitudes. Reduced light availability, soil temperatures, and water availability are all thought to limit nitrogen fixation due to its energetic costs, restricting nitrogen fixation plants to early successional communities at high latitudes. Shepherdia canadensis (buffalo berry) is an actinorhizal shrub found in higher latitudes across Canada, but little is known about its nitrogen fixation ecology. We determined how much nitrogen fixation occurs in buffalo berry and how nitrogen fixation varies with canopy cover at the northern edge of the boreal forest. Using the natural abundance of stable nitrogen isotopes, we found that S. candensis shrubs get 73 ± 8% of their nitrogen through fixation and that fixation is 10% higher in the forest compared to the tundra. Shrubs receiving more solar radiation produced thicker leaves with higher δ 13 C values, suggesting stomatal closure in response to reduced water availability. The change in leaf morphology makes leaves more efficient, allowing plants to maintain N fixation under increasing shade. However, N fixation in subarctic habitats is limited by water stress.
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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) | 0.001 | 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".