Nutrients and warming interact to force mountain lakes into unprecedented ecological states
Bibliographic record
Abstract
While deposition of reactive nitrogen (N) in the twentieth century has been strongly linked to changes in diatom assemblages in high-elevation lakes, pronounced and contemporaneous changes in other algal groups suggest additional drivers. We explored the origin and magnitude of changes in two mountain lakes from the end of the Little Ice Age at ca 1850, to ca 2010, using lake sediments. We found dramatic changes in algal community abundance and composition. While diatoms remain the most abundant photosynthetic organisms, concentrations of diatom pigments decreased while pigments representing chlorophytes increased 200–300% since ca 1950 and total algal biomass more than doubled. Some algal changes began ca 1900 but shifts in most sedimentary proxies accelerated ca 1950 commensurate with many human-caused changes to the Earth System. In addition to N deposition, aeolian dust deposition may have contributed phosphorus. Strong increases in summer air and surface water temperatures since 1983 have direct and indirect consequences for high-elevation ecosystems. Such warming could have directly enhanced nutrient use and primary production. Indirect consequences of warming include enhanced leaching of nutrients from geologic and cryosphere sources, particularly as glaciers ablate. While we infer causal mechanisms, changes in primary producer communities appear to be without historical precedent and are commensurate with the post-1950 acceleration of global change.
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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) | 0.002 | 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".