Spatial and seasonal variation in the phytoplankton community of Lake Victoria’s Mwanza Gulf, compared to northern parts of the lake
Bibliographic record
Abstract
We investigated the phytoplankton species composition and abundance in two seasons in Mwanza Gulf, Lake Victoria (Tanzania). Phytoplankton was sampled and chlorophyll a content was measured in the dry and wet seasons of 2010–2011 at three stations, from the southern land-inward end of the Gulf towards the open lake. Cyanobacteria, mostly small colonial and filamentous species (e.g., Aphanocapsa spp., Planktolyngbya spp., Merismopedia spp.) dominated at each station (76–95 %), followed by Chlorophyta (5–21 %), whereas the contribution of Bacillariophyceae was small (0–6 %). Phytoplankton densities were generally higher in the rainy season and strongly increased going land-inward from the open lake. Low abundance of N-fixing phytoplankton species suggests that N-fixation was low. The chlorophyll a content in the mouth of the Gulf was low (mean values 4–6 µg/L) compared to values reported previously. Also, chlorophyll a values (means 11–14 µg/L) at land-inward stations of Mwanza Gulf were much lower than those in the northern gulfs (Napoleon Gulf, Murchison Bay and Nyanza Gulf). Between 2002 and 2009 the phytoplankton composition of Mwanza Gulf changed from a community mostly dominated by Bacillariophyceae into a community dominated by Cyanobacteria. In the open water of Lake Victoria, Bacillariophyceae and Cyanobacteria were both abundant. Cyanobacteria dominated both in the three northern gulfs and Mwanza Gulf, but all four showed substantial differences in species and genus compositions. Phytoplankton composition and abundance in Mwanza Gulf differs in many respects from the open water of Lake Victoria and its three northern gulfs.
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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 | 0.000 |
| 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 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".