Nutrients and temperature additively enhance wood carbon fluxes
Bibliographic record
Abstract
The flux of CO2 from wood decomposition is a fundamental component of the global carbon cycle, but the impact of human-induced changes in temperature and nutrients on this flux is not well understood. We examined the effects of nitrogen and phosphorous addition on the temperature-dependence of CO2 fluxes from wood with differing traits (angiosperm and gymnosperm) over a three-year period. Results showed that CO2 fluxes were driven primarily by phosphorus and only secondarily by nitrogen, and that the effect of phosphorus was mediated by wood traits, with a greater increase in gymnosperms than angiosperms. The temperature dependences of CO2 fluxes were remarkably constant across nutrient levels, consistent with metabolic scaling theory hypotheses. These results suggest that phosphorus availability is a key driver of variation in wood CO2 fluxes, but has a limited impact on the temperature dependence. Our findings can inform predictions for wood carbon fluxes in a changing climate.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".