Incident Precipitation Partitioning: The Canopy Interactions Enrich Water Solution With Nutrients in Throughfall and Stemflow
Bibliographic record
Abstract
Atmospheric deposition is responsible for the ions input, which may be due to dust and aerosols and rainfall. During rainfall a portion is intercepted by the tree canopy and returned to the atmosphere by evapotranspiration, another part crosses the forest canopy called throughfall and stemflow. The objective of the present work was to quantify the nutrient input of the incident rainfall, throughfall, stemflow and canopy enrichment in an Eucalyptus dunnii plantation, established in soil with low natural fertility. Four plots of 20 m × 21 m were demarcated. The rainfall consists 3 rain collectors in an open área. The throughfall consisted 3 collectors per plot in the line, interlining and diagonal positions of the trees. The stemflow consisted in the installation of three systems per plot formed by a hose in the trunk of the tree that leads the solution to a reservoir. Through rainfall, 29.5 kg ha-1 of nutrients were supplied. When we consider the sum of the throughfall and stemflow, the amount of nutrients was 77.6 kg ha-1. After interaction with the tree canopy 48.2 kg ha-1 of nutrients were incorporated. Potassium showed the highest enrichment: 607%. The average nutrient enrichment was 163%. The input of N and K via incident rainfall was 1.8 and 3.1 kg ha-1. Considering the fertilization described in the methodology, this contributed amount represents 6.1 and 2.6% of the total. If we consider the rotation of 7 years for Eucalyptus dunnii, the contribution at the end of rotation represents 42.4 and 18% of N and K2O. The interaction with the canopy of Eucalyptus dunnii enriches the rainwater with nutrients making the solution with a more basic character.
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) | 0.001 | 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".