Neoglacial lake-ecosystem changes above and below the subarctic Fennoscandian treeline inferred from changes in diatom functional groups
Bibliographic record
Abstract
Abstract Algal communities act as sensitive indicators of past and present climate effects on northern lakes, but their responses can vary considerably between ecosystems. Functional trait-based approaches may help us better understand the nature of the diverse biotic responses and their underlying ecosystem changes. We explored patterns in diatom (Bacillariophyceae) growth forms and species composition during the Neoglacial in two shallow lakes typical of subarctic regions, including a dark-colored woodland lake and a clear tundra lake. Sediment carbon and nitrogen elemental and isotope biogeochemistry and spectral indices were used to track broadscale changes in lake productivity, the inflow of organic carbon from land, and benthic substratum over the past three millennia. The biogeochemical indices tracked declines in land-lake connectivity as well as lake-water and sediment organic enrichment above and below the subarctic treeline driven by Neoglacial cooling. This broadscale environmental transition was intercepted by periods of elevated primary production associated with transient Neoglacial warm anomalies and, in particular, the twentieth century warming. Although the Neoglacial development of the lakes showed conspicuous similarities, diatom functional and taxonomic responses were not uniform between the lakes pointing to intrinsic differences in the development of benthic habitats and underwater-light regimes. Many of the observed biotic shifts aligned with expectations based on earlier research linking diatom functional traits to changing light and organic levels but the results also point to further research needs, particularly to better differentiate the individual and interactive effects of substratum and light. Despite distinct anthropogenic imprints in the biogeochemical record, the scale of human impact on the lakes’ biota has not, as yet, been profound, but the changes are nonetheless clear when compared to the previous three millennia of natural lake development.
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 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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".