Specific diversity and abundance of communities of microcrustaceans and rotifers in two ponds, Mokolo and Mopa in the city of (Bertoua, Cameroon)
Bibliographic record
Abstract
One of the major challenges of aquatic ecology is to understand how anthropization affects biodiversity and what the consequences on the functioning of hydrosystems. Physicochemical and zoolanktonic variables studied in two ponds (Mokolo and Mopa) in the city of Bertoua, with two sampling stations (surface and depth) per pond and data collected monthly from March 2016 to April 2017 (14 months) allowed us to appreciate the spatial and seasonal dynamics of zooplankton in relation to anthropogenic disturbances. Abiotic variables of the ponds show that they are highly anthropized with relatively high temperatures (> 23 °C), low water transparency (< 70 cm) despite the shallow depth of the ponds (< 170 cm), average oxygenation (> 50%) with hypoxia (< 35%) recorded in the rainy season, high mineralization of the waters, high levels of nutrients, organic matter and photosynthetic pigments (> 30 µg/L). These characteristics allow to classify these water bodies in the category of hypereutrophic ponds. Biological data show fairly diverse ponds with 63 species identified in Mokolo Pond representing 17.89% of the total abundance. In Mopa Pond, 75 species were identified representing 21.30% of the total abundance. This study allowed us to deduce that the structure and dynamics of microcrustaceans communities are under the control of different processes that interact simultaneously. It is mainly influenced by the season, predation and by the depth of sampling, the month and the station having no influence on this distribution.
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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 | 0.001 | 0.001 |
| 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".