The physics of the warming of Lake Tanganyika by climate change
Bibliographic record
Abstract
Climate warming over the 20th century has increased the density stratification and stability of Lake Tanganyika, a deep rift valley lake. Here we examine the physical processes involved in and affected by the warming of the lake, and we discuss effects on lake productivity. The rate of net heat absorption by Lake Tanganyika has been 0.4 W m −2 since 1913, twice the rate in the global ocean, indicating stronger climate forcing in the East African region. Lakes warm through increased incoming long‐wave radiation. While lakes in general will increase heat outputs in a warming climate, heat outputs will increase more slowly in deeper lakes than in shallower lakes. Temperatures have increased by 0.2°C at 1000 m in depth, in part because of reduced cool marginal inflows, while water surface temperatures have increased by about 1.3°C. This differential heating over depth has increased the density gradient through the water column, reducing the potential for vertical mixing and thereby limiting nutrient fluxes to the phototrophic zone. An increase in transparency, indicating a reduction in productivity as a result of the reduced vertical mixing, occurred both in Lake Tanganyika and in Lake Malawi, a similar deep tropical lake in which warming has also been documented.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".