Spatial and Temporal Variation of Total Nitrogen and Total Phosphorus in Major River Systems of Sundarbans Mangrove Forest, Bangladesh
Bibliographic record
Abstract
Mangrove provides a unique ecological environment for diverse communities and Sundarbans is a rapidly changing ecosystem due to various anthropogenic activities. In order to assess the spatial and temporal variation of total Nitrogen and total Phosphorus concentration in Major River Systems of Sundarbans, a study was carried out from September, 2010 to February, 2011. Fourteen sampling location from major river systems were chosen. During post monsoon and winter seasons the range of total Phosphorus (0.326-0.409 mg/L and 0.091-0.371 mg/L respectively) and total nitrogen (2.52-3.50 mg/L and 3.43-5.25 mg/L respectively) were observed in Rupsha - Passur river system. On the other hand the range of total Phosphorus (0.475-0.144 mg/L and 0.060-0.113 mg/L respectively) and total nitrogen (2.31-3.61 mg/L and 3.22- 5.95 mg/L respectively) were found in Arpangashia - Malancha river system during post monsoon and winter seasons. The nutrients of water of Baleswar- Bhola river system during rainy and dry seasons were found in the range of total Phosphorus (0.106-0.364 mg/L and 0.053-0.075 mg/L respectively) and total nitrogen (2.59-3.57 mg/L and 2.87-5.60 mg/L respectively). Total Nitrogen and total phosphorus levels were relatively higher than the EPA standards for surface water during the two seasons. The Dynamic nutrients level observed in the study area may have severe consequences on the in-dwelling aquatic flora and fauna.
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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 | 0.001 | 0.001 |
| 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".