Thermal environment in an agroforestry system of coffee and rubber tree in Southern Brazil
Bibliographic record
Abstract
Climate change poses a significant risk to the production of Coffea arabica in currently cultivated areas, as the species has low tolerance to extreme temperature. Agroforestry systems are an alternative to contribute to the adaptation of this species and to continue the production in the regions where it is currently cultivated. This study assesses the thermal environment of an agroforestry system (AFS) composed of coffee and rubber trees (Hevea brasiliensis) planted in double rows with different spacings in Londrina, Parana state, Southern Brazil. Data of global solar radiation and temperature of air, leaves, and soil were continuously collected from 2015 to 2018. The findings reveal that the presence of rubber trees affected the microclimate by reducing extreme temperatures and decreasing mean temperatures. In the experimental conditions of limited size of the plots, leaf and soil temperatures represented more realistically the modifications in the microclimate induced by the rubber trees. The study concludes that this system can effectively contribute to the adaptation of coffee plantations in a warmer environment, in order to continue producing in traditional regions in Brazil.
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 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 | 0.000 | 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 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".