Transitions in Boreal Wetland Macroinvertebrate Community Composition Across a Natural Salinity Gradient
Bibliographic record
Abstract
Nearly 65% of Alberta’s northern boreal landscape is comprised of wetlands (primarily peatlands), which are lost in the process of open pit mining for oil sands. Demonstration wetlands recently created in reclaimed postmining watersheds are productive and support diverse biota. However, their water tends to be sodic due to the presence of salts in the soils used in their construction and residual sodium from the bitumen extraction process. Saline wetland systems occur in northern Alberta in areas where deep aquifer upwellings contribute significantly to a wetland’s water budget. I sampled the water chemistry and aquatic invertebrates in a suite of 52 pools ranging in specific conductance from 3,757 to 20,170 S/cm in a patterned fen southeast of Fort McMurray, Alberta, to identify patterns of community composition along the salinity gradient. Sodium, chloride, magnesium, and calcium were the dominant ions present in the saline fen. Pools with relatively low salinity supported abundant densities of gastropods and odonates whereas the most saline pools were dominated by Diptera larvae, especially genera of mosquitos. Threshold Indicator Taxon Analysis (TITAN) identified a set of 11 sensitive and 9 tolerant taxa diagnostic of specific conductivity. Community composition changed markedly at a threshold of 6,335-9,385 S/cm, equivalent to chloride concentrations of 1,579- 2,535mg/L. These findings may provide a useful frame of reference for anticipating community composition in wetlands forming in sodic areas of the reclaimed postmining landscape of the AOS.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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 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".