Functional diatom responses to Neoglacial environmental change in a dark and a clear shallow subarctic lake
Bibliographic record
Abstract
Algal communities in northern lakes respond sensitively to climate changes but their responses vary considerably between ecosystems. Functional approaches may help us better understand the nature of the biotic responses to environmental change, though presently this approach has rarely been used in northern lake environments. We explored patterns in diatom (Bacillariophyceae) species and functional composition during the Neoglacial in two shallow oligotrophic lakes typical of the Fennoscandian subarctic region. Sediment carbon and nitrogen isotope (δ13C, δ15N) and elemental biogeochemistry and spectral (visible-near infrared [VNIR] inferred lake-water total organic carbon [TOC] and sediment chlorophyll a) indices were used to track broad-scale environmental transitions over the past three millennia. A number of congruent change patterns were observed indicative of centennial to millennial scale changes in lake productivity, the inflow of organic carbon from land, and sediment organic carbon content. Both the dark colored woodland lake and the clear tundra lake displayed a gradual decline in lake water TOC concentrations attributed to Neoglacial cooling and transient increases in primary production associated with warmer periods and, in particular, the 20th century warming. Although the Neoglacial evolution of the lakes showed similarities, diatom functional responses were not uniform between the lakes. In the dark woodland lake, functional shifts appeared most strongly connected to declining lake-water TOC and sediment organic carbon content, and were reflected, most notably, as a decline in motile species affiliated with high organic levels and low-light conditions. In the clear tundra lake, changes in lake productivity and sediment organic carbon were reflected most distinctly in the abundance of attached and colonial life forms but the relationships were more ambiguous. While many of the observed shifts aligned with expectations based on earlier research linking diatom functional traits to changing light and organic carbon levels, discrepancies among the lakes and functional groups call for further refinement to detect ecologically meaningful traits in divergent aquatic environments. Both species and functional composition in the two lakes indicated that, despite distinct anthropogenic imprints in the biogeochemical record, human impact on the lakes’ diatoms has not, as yet, been profound.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".