The biogeochemistry of tropical lakes: A case study from Lake Matano, Indonesia
Bibliographic record
Abstract
We examined the chemical composition of the water column of Lake Matano, Sulawesi Island, Indonesia, to document how the high abundances of Fe (hydr)oxides in tropical soils and minimal seasonal temperature variability affect biogeochemical cycling in lakes. Lake Matano exhibits weak thermal stratification, yet a persistent pycnocline separates an oxic epilimnion from anoxic meta‐ and hypolimnions. The concentration of soluble P in the epilimnetic waters is very low and can be attributed to scavenging by Fe (hydr)oxides. Chromium concentrations in the epilimnion are high (up to 180 nmol L −1 ), but below U.S. Environmental Protection Agency guidelines for aquatic ecosystems. The concentration of chromium decreases sharply across the oxic‐anoxic boundary, revealing that the hypolimnion is a sink for Cr. Flux calculations using a one‐dimensional transportreaction model for the water column fail to satisfy mass balance requirements and indicate that sediment transport and diagenesis play an important role in the exchange of Fe, Mn, P, and Cr between the epilimnion and hypolimnion. Exchange of water between the epilimnion and hypolimnion is slow and on a time scale similar to temperate meromictic lakes. This limits recycling of P and N to the epilimnion and removal of Cr to the hypolimnion, both of which likely restrict primary production in the epilimnion. Owing to the slow exchange, steep concentration gradients in Fe and Mn species develop in the metalimnion. These concentration gradients are conducive to the proliferation of chemoautotrophic and anoxygenic phototrophic microbial communities, which may contribute a significant fraction to the total primary production in the lake.
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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 | 0.001 | 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".