Climate Change Forces New Ecological States in Tropical Andean Lakes
Bibliographic record
Abstract
Air temperatures in the tropical Andes have risen at an accelerated rate relative to the global average over recent decades. However, the effects of climate change on Andean lakes, which are vital to sustaining regional biodiversity and serve as an important water resource to local populations, remain largely unknown. Here, we show that recent climate changes have forced alpine lakes of the equatorial Andes towards new ecological and physical states, in close synchrony to the rapid shrinkage of glaciers regionally. Using dated sediment cores from three lakes in the southern Sierra of Ecuador, we record abrupt increases in the planktonic thalassiosiroid diatom Discostella stelligera from trace abundances to dominance within the phytoplankton. This unprecedented shift occurs against the backdrop of rising temperatures, changing atmospheric pressure fields, and declining wind speeds. Ecological restructuring in these lakes is linked to warming and/or enhanced water column stratification. In contrast to seasonally ice-covered Arctic and temperate alpine counterparts, aquatic production has not increased universally with warming, and has even declined in some lakes, possibly because enhanced thermal stability impedes the re-circulation of hypolimnetic nutrients to surface waters. Our results demonstrate that these lakes have already passed important ecological thresholds, with potentially far-reaching consequences for Andean water resources.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".