CHANGES IN SOIL PH, POLYPHENOL CONTENT AND MICROBIAL COMMUNITY MEDIATED BY EUCALYPTUS CAMALDULENSIS
Bibliographic record
Abstract
Eucalyptus camaldulensis has been the main exotic species planted in reforestation programs in the tropics due to its fast growth and adaptability to climate variations.Based on the premise that the conversion from natural grazed pastures to commercial Eucalyptus plantations generates significant changes in soil properties, we assessed the impact of this exotic plantation on soil chemical and biological indicators.The study was conducted in 6 plantations across Senegal following a decreasing rainfall gradient from south to north.The plantations were divided in three lots according to their age: young plantations (established in 2003, 6 years old); intermediate plantations (established in 1998, 11 years old) and old plantations (established in 1982 and 1983, 26 years old).Our results clearly showed that E. camaldulensis plants significantly modified soil pH and soil bacterial community at all sites regardless of the age of the plantation.Microbial biomass (assessed by substrate-induced respiration), community structure (assessed by denaturing gradient gel electrophoresis profiles) and function (assessed by Catabolic Response Profile using different substrates) were all significantly decreased.The acidifying effect of E. camaldulensis, the effect of high level of polyphenols and their impact on microbial communities and ecosystem functioning were discussed.
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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 | 0.000 |
| 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".