PERIPHYTIC DIATOM ASSEMBLAGES FROM BATHURST ISLAND, NUNAVUT, CANADIAN HIGH ARCTIC: AN EXAMINATION OF COMMUNITY RELATIONSHIPS AND HABITAT PREFERENCES
Bibliographic record
Abstract
Diatoms are potentially the most important biomonitors of environmental change in high arctic lakes and ponds, but to date few autecological data are available. Because of the shallow nature of many of these water bodies, a large proportion of taxa are periphytic and planktonic diatoms are absent for the most part. By determining the microhabitat and substrate preferences of these benthic diatom taxa, the potential exists to infer past changes in available habitats from fossil diatom assemblages collected from sediment cores and ultimately to reconstruct past environmental and climatic changes responsible for these shifts in habitat availability. To refine our understanding of high arctic diatom habitat preference, the common diatom taxa found on submerged moss (bryophyte), sediment, and rock substrates from lakes and ponds on Bathurst Island, Nunavut, Canadian High Arctic were examined. The relationships among key limnological variables and the common taxa from each habitat were examined. Many diatom taxa exhibited varying degrees of microhabitat preference, with moss representing the more unique habitat. In addition, the following limnological variables significantly (P≤ 0.05) explained the species variance for each of the three substrates: Na+ and total nitrogen for moss; total phosphorus (filtered) and pH for rock; and Fe3+, total phosphorus (unfiltered), total nitrogen, temperature, and pH for sediment. These data can be used to help interpret monitoring and paleolimnological studies in this environmentally sensitive region.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".