The Influence of Cellulolytic Bacteria on Soil Properties in Mangrove Ecosystems of Banda Aceh and Aceh Besar, Indonesia
Bibliographic record
Abstract
Mangrove ecosystems harbor diverse bacterial communities that significantly affect soil properties.Among these bacteria are cellulolytic species, which contribute to the breakdown of organic matter.This study aimed to analyze the total population of cellulolytic bacteria and their relationship with soil characteristics in mangrove ecosystems along the coast of Banda Aceh and Aceh Besar, Aceh Province, Indonesia.Six research locations were selected, with soil samples taken at three depth intervals: 0-15 cm (Layer 1), 15-30 cm (Layer 2), and 30-45 cm (Layer 3).The total population of cellulolytic bacteria was found to vary depending on both sampling location and soil depth.The highest total population of bacterial colonies was observed at location 2.3.However, on average, the soil surface (Layer 1) harbored a higher number of cellulolytic bacteria (13.0×10 7 CFU g -1 dry soil) compared to Layers 2 and 3 (5.0×107 and 8.0×10 7 CFU g -1 dry soil, respectively).A significant correlation was observed between the total bacterial population and organic carbon content (P < 0.05), while no significant correlations were found with soil particle size, pH, salinity, total nitrogen, available phosphorus, or soil moisture (P > 0.05).Unrehabilitated mangrove ecosystems exhibited higher levels of cellulolytic bacterial populations, sand and silt fractions, pH, salinity, organic carbon, total nitrogen, and moisture compared to rehabilitated mangrove ecosystems.
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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 | 0.001 | 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".