Nitrogen cycling in canopy soils of tropical montane forests responds rapidly to indirect N and P fertilization
Bibliographic record
Abstract
Although the canopy can play an important role in forest nutrient cycles, canopy-based processes are often overlooked in studies on nutrient deposition. In areas of nitrogen (N) and phosphorus (P) deposition, canopy soils may retain a significant proportion of atmospheric inputs, and also receive indirect enrichment through root uptake followed by throughfall or recycling of plant litter in the canopy. We measured net and gross rates of N cycling in canopy soils of tropical montane forests along an elevation gradient and assessed indirect effects of elevated nutrient inputs to the forest floor. Net N cycling rates were measured using the buried bag method. Gross N cycling rates were measured using (15) N pool dilution techniques. Measurements took place in the field, in the wet and dry season, using intact cores of canopy soil from three elevations (1000, 2000 and 3000 m). The forest floor had been fertilized biannually with moderate amounts of N and P for 4 years; treatments included control, N, P, and N + P. In control plots, gross rates of NH4 (+) transformations decreased with increasing elevation; gross rates of NO3 (-) transformations did not exhibit a clear elevation trend, but were significantly affected by season. Nutrient-addition effects were different at each elevation, but combined N + P generally increased N cycling rates at all elevations. Results showed that canopy soils could be a significant N source for epiphytes as well as contributing up to 23% of total (canopy + forest floor) mineral N production in our forests. In contrast to theories that canopy soils are decoupled from nutrient cycling in forest floor soil, N cycling in our canopy soils was sensitive to slight changes in forest floor nutrient availability. Long-term atmospheric N and P deposition may lead to increased N cycling, but also increased mineral N losses from the canopy soil system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".