Vegetation transitions drive the autotrophy–heterotrophy balance in Arctic lakes
Bibliographic record
Abstract
Abstract “Arctic greening” will alter vegetation quantity and quality in northern watersheds, with possible consequences for lake metabolic balance. We used paleolimnology from six Arctic lakes in Greenland, Norway, and Alaska to develop a conceptual model describing how climate‐driven shifts in terrestrial vegetation (spanning herb to boreal forest) influence lake autotrophic biomass (as chlorophyll and carotenoid pigments). Major autotrophic transitions occurred, including (1) optimal production of siliceous algae and cyanobacteria/chlorophytes at intermediate vegetation cover (dwarf shrub and Betula ; dissolved organic carbon (DOC) range of 2–4 mg L −1 ), below and above which UVR exposure (DOC; < 2 mgL −1 ) and light extinction (DOC; > 4 mgL −1 ), respectively limit algal biomass, (2) an increase in potentially mixotrophic cryptophytes with higher forest cover and allochthonous carbon supply. Vegetation cover appears to influence lake autotrophs by changing influx of (colored) dissolved organic matter which has multiple interacting roles—as a photoprotectant—in light attenuation and in macronutrient (carbon, nitrogen) supply.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| 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 teacher head, 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".