Plankton Distribution and Diversity in Tropical Earthen Fish Ponds
Bibliographic record
Abstract
Our knowledge of the consumption of plankton by fish is still fragmentary. Trophic links between fish and plankton are often loose because plankton is a changing assemblage of pelagic organisms of valuable nutritional value. The objectives of the study were to determine the distribution and diversity of planktons in the fish ponds. Water samples for plankton analysis were collected monthly (January-December), along with water samples used for the determination of physico-chemical parameters in 250 ml bottles in Ponds 1, 2 and 5. The freshwater sample was mixed gently and pipetted into 5 ml plankton chamber containing 2 drops of Lugol’s solution. The Lugol’s solution which served as fixative also enhanced sedimentation of the organisms and was left overnight before analyzing plankton using Zeiss inverted plankton microscope and plankton determination keys. Data was analyzed using Shannon-Weaner diversity index, species richness, means and analysis of varians (ANOVA). The results showed that the highest species richness for dry season phytoplankton value of 27 was recorded in Pond 2, with the highest Shannon-Weaner diversity index value of 0.5401 in pond 5. Merismopaedia elegans with 3,434 in pond 2 was the most abundant phytoplankton species and chlorophyceae the most dominant taxa. The rainy season zooplankton species richness values (5 in pond 2) were higher than that of the dry season (3 in pond 3) with the highest Shannon-Weaner index value of 0.3501 recorded in pond 1. The most abundant zooplankton species Asplanchna species 57 was recorded in pond 2. Significant differences (p < 0.05) was observed for phytoplankton and zooplankton species between the ponds. Physico-chemical parameters had influence on the distribution and diversity of planktons in the fish ponds.
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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 | 0.001 |
| 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 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".