Seasonal patterns of climate controls over nitrogen fixation by <i>Alnus viridis</i> subsp. <i>fruticosa</i> in a secondary successional chronosequence in interior Alaska
Bibliographic record
Abstract
Patterns of and controls over N2 fixation by green alder were studied in post-fire, mid-succession, and white spruce upland forests in interior Alaska, focusing on the hypothesis that ecosystem-level nitrogen (N) inputs decrease with successional development. N2-fixation rates tracked plant phenology during the 1997 (drought) and 1998 (normal precipitation) growing seasons. The best model for predicting acetylene reductase activity (ARA, μmol C2H4·g noduleDWT−1·h−1) across all stands and sampling periods included a linear response to soil temperature and a quadratic response to Julian day (r2 = 0.23, P < 0.0001). There were few significant relationships between seasonal maximum values for ARA and measured leaf traits; however, we did detect an inverse correlation between foliar N to P ratio and seasonal maximum ARA. During 1998, stands with higher maximum ARA had higher soil %N, and maximum ARA was positively correlated with subcanopy %P in O and A soil horizons. During 1997, leaf %P and N resorption were lower and leaves were thinner compared to 1998. Drought effects were most pronounced in mid-succession, where alder exhibited reduced ARA, leaf %P, leaf thickness, and lower leaf resorption of P and N. Although ARA and nodule biomass did not differ among stand types, increases in alder densities with successional time translated to increasing ecosystem-level N inputs across the chronosequence. These results contradict established theory predicting a decline in N2-fixation rates and N2-fixer abundance during successional stand development.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".