Effects of Nile Tilapia (<i>Oreochromis niloticus</i>) on phytoplankton community structure and water quality: a short-term mesocosm study
Bibliographic record
Abstract
Nile tilapia is a highly invasive fish species, deliberately introduced into many lakes and reservoirs worldwide, sometimes resulting in significant ecosystem alterations. A short-term mesocosm experiment with and without Nile tilapia (Oreochromis niloticus) was designed to test the hypotheses that the presence of tilapia may affect phytoplankton community structure, increase nutrients availability in water column and deteriorate water quality. Nutrients, total suspended solids (TSS) and biomass of phytoplankton in different size classes (as Chla) were measured. We found that tilapia increased the total nitrogen (TN), total dissolved nitrogen (TDN), NH4+and TSS concentrations, deteriorating the water quality. In addition, under tilapia presence, the biomass of phytoplankton, as well as that of micro- and nano-phytoplankton, increased leading to a change in the structure of the phytoplankton assemblage. Moreover, a reduction in the biomass of periphyton was observed. Omnivorous tilapia is often dominant in tropical and subtropical waters, and removal of this fish may represent an effective management tool to improve the water quality.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".