Abrupt changes in the physical and biological structure of endorheic upland lakes due to 8‐m lake‐level variation during the 20<sup>th</sup> century
Bibliographic record
Abstract
Abstract Climate‐induced variation in lake level can affect physicochemical properties of endorheic lakes, but its consequences for phototrophic production and regime shifts are not well understood. Here, we quantified changes in the abundance and community composition of phototrophs in Kenosee and White Bear lakes, two endorheic basins in the parkland Moose Mountain uplands of southeastern Saskatchewan, Canada, which have experienced > 8 m declines in water level since ~ 1900. We hypothesized that lower water levels and warmer temperatures should manifest as increased abundance of phytoplankton, particularly cyanobacteria, and possibly trigger a regime shift to turbid conditions due to evaporative concentration of nutrients and solutes. High‐resolution analysis of sedimentary pigments revealed an increase in total phototrophic abundance (as β‐carotene) concurrent with lake‐level decline beginning ~ 1930, but demonstrated little directional change in cyanobacteria. Instead, significant increases in obligately anaerobic purple sulfur bacteria (as okenone) occurred in both lakes during ~ 1930–1950, coeval with alterations to light environments and declines in lake level. The presence of okenone suggests that climate‐induced increases in solute concentrations may have favored the formation of novel bacterial habitats where photic and anoxic zones overlapped. Generalized additive models showed that establishment of this unique habitat was likely preceded by increased temporal variance of sulfur bacteria, but not phytoplankton or cyanobacteria, suggesting that this abrupt change to physical lake structure was unique to deep‐water environments. Such climate‐induced shifts may become more frequent in the region due to hydrological stress on lake levels due to warming temperatures across the Northern Great Plains.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".