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Record W7036730384

Controls of Wetland Hydrology in the Zone of Discontinuous Permafrost, Northwest Territories, Canada

2025· article· en· W7036730384 on OpenAlexaboutno aff

Bibliographic record

VenueScholars Commons (Wilfrid Laurier University) · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPhytochemistry and Biological Activities
Canadian institutionsnot available
Fundersnot available
KeywordsPermafrostWetlandHydrology (agriculture)Water balanceSurface runoffDrainage basinStructural basinClimate changeWater storageLand cover
DOInot available

Abstract

fetched live from OpenAlex

Mean annual air temperatures are increasing rapidly in northwestern Canada, which is among the most rapidly warming regions on Earth (Box et al., 2019). Consequently, permafrost thaw within northwestern Canada is proceeding at a rate not found in the historical record (Pelletier et al., 2017), with areal thaw rates especially high in the peatland-dominated southern margin of discontinuous permafrost (Quinton et al., 2019). Permafrost thaw has caused vast land cover changes and transformed the permafrost underlain forest into permafrost free wetlands over much of Taiga Plains (Carpino et al., 2018; Jorgenson & Osterkamp, 2005). This land cover change has altered how water is stored and cycled on the landscape (Haynes et al., 2018). These changes were driven by the expansion of runoff contributing areas, as permafrost “barriers” are removed with thaw (Connon et al., 2014). This process effectively taps water stored in the interior of plateau-wetland complexes. Considering the changes that occurred within these wetland complexes, an updated wetland basin area found that not only had the contributing area has expanded but the wetland basin had grown with the inclusion of additional wetlands to the wetland cascade. However, proportionally the forest to wetland ratio has remained the same at almost equal proportions. This study examined the inter-annual variability of water balance components for each year from 2013 to 2022 for a 11.2 hectare plateau-wetland complex. Further narrowing into a detailed wetland-based water balance for 2022, examining the intra- annual variation of water storage within the collapse scar wetland W-3. The summer of 2022 (April 1 – September 30) was characterized with an extremely low rainfall (103 mm) and deep late winter snowpack (240 mm). Subsurface hillslope runoff from the surrounding forest was the greatest flux of water into the wetland (249 mm). Although subsurface runoff varies over time, a conceptual model is presented with the inclusion of the capillary fringe as an area of intermediary water storage and transport. Overland flow between wetland was the greatest water loss mechanism for the wetland (487 mm) and was greatest during the spring freshet with 81% of the total overland flow occurring during this period, although discharge was greatly reduced post-freshet. Evapotranspiration was the second largest source of water loss within the wetland (294 mm), by June 1 evapotranspiration was the predominant source of water loss. This led to a large wetland water deficit by the end of September (-177 mm). The extreme hydrological events of 2022 are used to identify the critical thresholds of the water balance components. This study furthered our understanding on how water movement and storage within wetlands will change with continued permafrost loss. When the critical thresholds of water balance components are exceeded, the integrity of wetlands within the region is threatened.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.685
Threshold uncertainty score0.785

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.179
Teacher spread0.172 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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