Climate drivers of diatom distribution in shallow subarctic lakes
Bibliographic record
Abstract
Abstract Global warming can induce profound changes to the functioning of northern freshwater ecosystems. Diatom (Bacillariophyceae) communities often provide early warning signs of associated ecological regime shifts, responding sensitively to alterations in underwater light climate, nutrient regimes, habitat availability and lake water acid–base balance. The underlying mechanisms are manifold and may be mediated via direct climate impact on the physical and chemical properties of lakes or via changes in the terrestrial environment and catchment‐lake coupling. To address catchment‐mediated climate effects on diatom community composition, spatial diatom distribution in the surface sediments of 31 subarctic treeline lakes displaying a broad gradient in terrestrial dissolved organic matter ( tDOM ) was contrasted with limnological indices of light climate, nutrient availability and lake water pH . To evaluate direct and indirect climate impacts on the long‐term development of benthic phototrophic communities at the subarctic treeline, fossil diatom assemblages in the sediments of a shallow oligotrophic lake were examined against established temperature variability and inferences of terrestrial influence over the past 600 years. The regional lake set was used to test local calibration models for reconstructing dissolved organic carbon as well as lake water pH that is a fundamental environmental determinant for diatom distribution and may echo temperature variability in dilute lakes. Across the treeline, lake water pH imposed primary control over the benthic‐dominated surface sediment diatom communities. The pH influence was connected to catchment geomorphology, soils and vegetation cover and, together with habitat controls, largely superseded tDOM impact on underwater light attenuation and nutrient levels. Similarly, temporal changes in diatom distribution in the sediment core appeared to be relatively little affected by tDOM variability. The species shifts were subtle yet occurred in distinct synchrony with centennial temperature fluctuations, attributed to changing length of the ice cover period and associated effects on lake water chemistry, nutrient regimes and physical habitats. Our results suggest that diatom flora in shallow lakes at the subarctic Fennoscandian treeline may be comparatively resilient towards climate‐driven changes in terrestrial carbon and nutrient fluxes. Diatom communities in poorly buffered lakes may, however, be susceptible to catchment greening and changes in hydrology through effects on lake water acid–base balance. While diatom responses in the sediment sequence were subtle, the palaeolimnological record indicates that periphytic diatom communities in shallow oligotrophic subarctic lakes may be sensitive to the effects of global warming.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".