Multidisciplinary approach to identify aquifer-peatland connectivity.
Bibliographic record
Abstract
In southern Quebec (Canada), wetlands sustain increasing pressures from agriculture, urban development, and \npeat exploitation. To protect both groundwater and ecosystems, it is important to be able to identify how, where, \nand to what extent shallow aquifers and wetlands are connected. This study focuses on peatlands which are especially \nabundant in Quebec. The objective of this research was to better understand aquifer-peatland connectivity \nand to identify easily measured indicators of this connectivity. Geomorphology, hydrogeochemistry, and vegetation \nwere selected as key indicators of connectivity. Twelve peatland transects were instrumented and monitored \nin the Abitibi (slope peatlands associated with eskers) and Centre-du-Quebec (depression peatlands) regions of \nQuebec (Canada). Geomorphology, geology, water levels, water chemistry, and vegetation species were identified/ \nmeasured on all transects. Flow conditions were simulated numerically on two typical transects. Results show \nthat a majority of peatland transects receives groundwater from a shallow aquifer. In slope peatlands, groundwater \nflows through the organic deposits towards the peatland center. In depression peatlands, groundwater flows only \n100-200 m within the peatland before being redirected through surface routes towards the outlet. Flow modeling \nand sensitivity analysis have identified that the thickness and hydraulic conductivity of permeable deposits close \nto the peatland and beneath the organic deposits influence flow directions within the peatland. Geochemical data \nhave confirmed the usefulness of total dissolved solids (TDS) exceeding 14 mg/L as an indicator of the presence \nof groundwater within the peatland. Vegetation surveys have allowed the identification of species and groups of \nspecies that occur mostly when groundwater is present, for instance Carex limosa and Sphagnum russowii. Geomorphological \nconditions (slope or depression peatland), TDS, and vegetation can be measured/observed with \nlimited effort in the field. Results from this study have the potential to help water managers and decision makers \nbetter understand and characterize aquifer-peatland interactions.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".