Reconstruction of Holocene hydroclimatic variability in subarctic treeline lakes using lake sediment grain-size end-members
Bibliographic record
Abstract
Current climate trends are expected to result in the northward expansion of the subarctic treeline leading to changes in vegetation cover and permafrost distribution, as they did during the Holocene Climate Optimum when the treeline was 150 km north of its current position. The impacts of these changes on the region’s hydrology are still poorly understood. The grain-size distributions of treeline lake sediments provide an important proxy related to spring melt conditions that can be used to reconstruct hydroclimatic variability. End-member mixing analysis was used to model depositional end-members in 55 modern lake sediment samples and two sediment cores spanning the mid- to late Holocene collected from above and below the treeline in the central Northwest Territories, Canada. Cold climatic intervals (e.g. ‘Dark Ages Cold Period’, ‘Little Ice Age’) were characterised by an increase in the very coarse silt and the fine sand end-members. This was interpreted to be a response to degradation of vegetation cover and/or permafrost development. We observed increases in fine and coarse silt end-members during warmer climatic intervals (e.g. Medieval Climate Anomaly) and over the past c. 300 yr BP. This pattern is probably the result of extended melt seasons, with greater losses to evaporation and increased infiltration. The most pronounced palaeo-hydroclimatological change over the past c. 8000 yr BP was the abrupt increase in a very coarse silt end-member (mode = 50–200 µm) at c. 6300 yr BP. We interpreted the sedimentological change as an increase in winter precipitation and more energetic spring melt conditions, leading to the spring melt becoming the dominant lacustrine sediment delivery mechanism. These results place modern hydrological changes in a millennial context and show that analysis of temporal changes in the hydroclimatological system can provide insight into the future states of these sensitive subarctic ecosystems.
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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 | 0.003 | 0.001 |
| 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) | 0.004 | 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".