The relation between sediment nutrient content and macrophyte biomass and community structure along a water transparency gradient among lakes of the Mackenzie Delta
Bibliographic record
Abstract
Macrophyte abundance and distribution among lakes of the Mackenzie Delta were assessed where increasing distance from the river (chain set) and increasing frequency of flooding (sill set) corresponded with increasing water transparency. Overall, sediment organic matter (OM) and total nitrogen (TN) content increased with increasing biomass of macrophytes but was higher in the sill set than in the chain set. The amount of phosphorus (P) in sediments was similar among lakes, but pore-water P was appreciably higher in the chain set. Increasing sediment OM and water clarity corresponded with increasing biomass of macrophytes in the lakes. Community structure shifted from dominance by erect Potamogeton at low and intermediate transparency and moderate sediment OM content to low-growing Chara and Ceratophyllum at high transparency and high sediment OM. Similar transparency in the chain set supported greater biomass of macrophytes than in the sill set. A high rate of inorganic sedimentation (linked with frequent flooding) and organic sedimentation (linked with high transparency and plant biomass) may result in the most suitable substrate for the growth of macrophytes among lakes of the Mackenzie Delta. Submersed plant biomass was higher in the Mackenzie Delta lakes than in temperate lakes and comparable to that in the temperate and tropical floodplains, despite the high-latitude location.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".