Relationships among litterfall, fine-root growth, and soil respiration for five tropical tree species
Bibliographic record
Abstract
Although significant advances have been made in understanding terrestrial carbon cycling, there is still a large uncertainty about the variability of carbon (C) fluxes at local scales. Using a carbon mass-balance approach, I investigated the relationships between fine detritus production and soil respiration for five tropical tree species established on 16-year-old plantations. Total fine detritus production ranged from 0.69 to 1.21 kg C·m–2·year–1with significant differences among species but with no correlation between litterfall and fine-root growth. Soil CO2emissions ranged from 1.61 to 2.36 kg C·m–2·year–1with no significant differences among species. Soil respiration increased with fine-root production but not with litterfall, suggesting that soil C emissions may depend more on belowground inputs or that both fine root production and soil respiration are similarly influenced by an external factor. Estimates of root + rhizosphere respiration comprised 52% of total soil respiration on average, and there was no evidence that rhizosphere respiration was associated with fine-root growth rates among species. These results suggest that inherent differences in fine-root production among species, rather than differences in aboveground litterfall, might play a main role explaining local-scale, among-forest variations in soil C emissions.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".