Assessment Of 2022 Flood Effects On Ichthyofauna, Water Quality Parameters And Heavy Metals Level At The Confluence Of River Swat And River Panjkora, KP, Pakistan
Bibliographic record
Abstract
The present study was designed to investigate the effects of the 2022 flood on fish distribution and water quality at the confluence of River Swat and River Panjkora at Bosaq Malakand, Khyber Pakhtunkhwa, Pakistan from October to March 2023. During the study period, a total of 437 fish specimens were collected belonging to 2 orders, Cypriniformes and Siluriformes, 3 families, Cyprinidae, Sisoridae, and Garinidae, 7 genera, and 7 species i.e., Racoma labiata, Orienus plagiostomus, Glyptothorax cavia, Carassius auratus, Garra gotyla, Labeo dyocheilus pakistanicus, and Tor putitora. The family Cyprinidae was the most diverse family represented by 5 species, whereas Orienus plagiostomus was the most abundant species. The comparative physico-chemical parameters of water were also studied, which were taken from four different sites. The values for water temperature were 7.7-9°C, pH 6.98-7.42, dissolved oxygen 8.5-8.9 mg/l, alkalinity 215-240 mg/l, electrical conductivity 232-238µs, TDS 91-125 ppm, TSS 200-500 mg/l, Total hardness 116-129.98 mg/l, Calcium hardness 73-99.99 mg/l, Magnesium hardness 23-56.7 mg/l, Sodium 3.2-3.7 ppm, Potassium 30-30.4 ppm, Chlorides 15-32.03 mg/l and turbidity of water ranged from 0 to2-12 NTU. After the flood, 2 fish species were not reported from the studied area i.e. Mastacembelus armatus and Chela cachius, which means that the flood has swept away their fingerlings as well as adults. All the water parameters were within normal range during the study period except for the values of Alkalinity, Potassium, TSS, and Turbidity, which were higher than the permissible range. This might be due to floods and low water levels during the study period. Analysis: Heavy metals showed that chromium was higher than permissible limits recommended by WHO recommended standards while the other heavy metals were within the permissible limits. Therefore, it can be concluded that the water in the area is suitable for fish and aquatic life, and fish culture could be promoted in the area.
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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 | 0.001 | 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".