Water Table Depth and Vapour Pressure Deficit Interaction Drives Bare Peat Evaporation at Actively Extracted Peatlands in Canada
Bibliographic record
Abstract
ABSTRACT Peat extraction alters the hydrophysical properties of the peat during the 15 to 40 plus years of extraction. Despite the importance of hydrologic conditions for driving carbon (C) emissions from this net C source, few studies in Canada have quantified the impact of peat extraction on energy partitioning and evaporation (E) rates. The removal of vegetation prior to extraction alters the controls and mechanisms of water loss, and drainage‐induced subsidence is expected to enhance vertical capillary connectivity through the peat profile. We thus conducted a multi‐year study using eddy covariance to understand the energy balance and daytime E rates from actively extracted sites in Quebec and Alberta, Canada. Despite being a partially drained system, available energy was largely partitioned into latent heat. The relative importance of surface and atmospheric controls of E varied with hydrologic conditions; with greater water table depth (WTD), the relative importance of vapour pressure deficit decreased, and the relative importance of WTD increased. Our results highlight a need for continuous surface moisture measurements for accurate E prediction. During active extraction, site managers harrow (till) the top few cm of peat to create a drier, hydrologically isolated layer that is then extracted and processed. A weighing bucket lysimeter experiment found that while harrowing initially elevated E rates, by ~4 h post harrowing, the newly dry layer acted as a barrier to further water loss from the peat profile. These sites provide a unique opportunity to further our understanding of water availability and transport of water to the evaporating surface from bare peat, and will inform future modelling efforts to partition evapotranspiration from peatlands. An understanding of the impact of site management on E rates informs site water balance calculations and can aid in optimizing harvesting practices and effective restoration strategies post‐extraction.
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 | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 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".