Diatom Changes in Lake Sediments from the Mackenzie Delta, N.W.T., Canada: Paleohydrological Applications
Bibliographic record
Abstract
Information on hydrological fluctuations and lake dynamics in the Mackenzie Delta in Arctic Canada is provided in a paleolimnological study of eight delta lakes. Because macrophyte production within Mackenzie Delta lakes is largely governed by the degree of river influence, estimates of past production within a lake may be used to infer past Mackenzie River influence. A diatom-based predictive model, using sub-ice winter methane concentrations as an indirect estimate of macrophyte production, was applied to fossil diatom assemblages identified in Mackenzie Delta lake sediment cores. Temporal shifts in the relative abundance of fossil diatom assemblages were recorded at all sites. Benthic and epiphytic fossil diatom taxa were common in lakes with minor river influence, whereas planktonic species dominated lakes with appreciable river connection. The fossil diatom record indicated that taxa are responding to changes in the degree of river influence and lake genesis. Lakes having the least amount of river connection supported the most favorable environment for macrophyte production, resulting in the highest sediment organic matter content, and consequently, the highest estimates of methane concentrations. In general, the diatom-inferred winter methane concentrations appeared to be reliable, and they indirectly track the main direction of variation in the fossil diatom assemblages. The lack of consistent trends between sites in diatom assemblage changes/inferred methane values indicates that the hydrology near Inuvik, although highly variable, has not undergone a steady-state shift over the past ~200 yr. However, our results do indicate that diatom taxa in delta lakes are sensitive to hydrological fluctuations in the Mackenzie River and that our present approach would be ideally suited for detecting longterm (e.g., decadal) hydrological variations.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".