Diatoms as indicators of hydrologic and climatic change in saline lakes
Bibliographic record
Abstract
Introduction Lakes are intricately tied to the climate system in that their water level and chemistry are a manifestation of the balance between inputs (precipitation, stream inflow, surface runoff, groundwater inflow) and outputs (evaporation, stream outflow, groundwater recharge) (Mason et al ., 1994). Hence, changes in a lake's hydrologic budget caused by climatic change have the potential to alter lake level and lake chemistry. These changes, in turn, may affect the physiological responses and species composition of the lake's biota, including diatoms. Here we review the use of diatoms as indicators of hydrologic and climatic change, with an emphasis on environmental reconstruction in arid and semi-arid regions. First we discuss linkages among climate, hydrology, lake hydrochemistry, and diatoms that form the foundation for environmental reconstruction, and then we review selected examples of diatom-based studies. Lake hydrology and hydrochemistry Lakes vary in their hydrologic sensitivity to climatic change (Winter, 1990). In basins with a surface outlet, lake-level increase is constrained by topography, and any change in input is usually balanced by outflow. Thus, in open basins, lake level fluctuates relatively little, unless hydrologic change is sufficiently large to drop water level below the outlet level. In contrast, closed-basin lakes without surface outflow often show changes in level associated with changes in the balance between precipitation and evaporation (P – E).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".