Long-term study of the drought impact on the phytoplankton concentration and assemblages in two water supply reservoirs in Namibia
Bibliographic record
Abstract
Rising temperatures and increased occurrences of droughts, brought on by climate change, are expected to affect reservoir water levels. We hypothesised that the decrease in reservoir volumes in dams with desert climates will favour the growth of phytoplankton biomass, measured as chlorophyll a (Chl a), under drought conditions. Using the threshold levels method of Q50, ten drought years were recorded in the Von Bach Dam (VB) in comparison to seven in the Swakoppoort Dam (SWP). Both dams had significant reduction in percentage volume (vol %). The Chl a in SWP was 81 µg l−1 in drought and 48 µg l−1 in AAR years, compared to VB with 21 µg l−1 in drought and 24 µg l−1 in AAR years. Cyanobacterial cell counts in drought and AAR years in SWP were 129 704 and 77 838 cells ml−1, respectively, while cell counts in drought and AAR years in VB were 5 925 cells ml−1 and 20 070 cells ml−1, respectively. Decreases in phytoplankton biomass and total cyanobacteria were observed in SWP but not in VB. The pattern and magnitude of the statistically significant responses (t-test, p < 0.05) between physico-chemical and biological water quality variables varied among drought and AAR years. We conclude that that there is no clear correlation between drought and phytoplankton biomass from this study and that other anthropogenic–environmental drivers, such as land use impacts, will be needed to further elucidate the response of water quality to droughts.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 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".