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Record W3015883924 · doi:10.1002/eco.2210

Ecohydrological change following rewetting of a deep‐drained northern raised bog

2020· article· en· W3015883924 on OpenAlexaff
Paul P.J. Gaffney, Sandrine Hugron, Sylvain Jutras, Olivier Marcoux, Sébastien Raymond, Line Rochefort

Bibliographic record

VenueEcohydrology · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsSphagnumBogDitchPeatEnvironmental scienceHydrology (agriculture)Water tableBiogeochemical cycleEcosystemMossVegetation (pathology)EcologyGeologyGroundwaterBiology

Abstract

fetched live from OpenAlex

Abstract Restoration of degraded peatland ecosystems (by rewetting) is undertaken to bring back key ecosystem services. However, the restoration process can have a range of ecohydrological effects, due to the associated physical and biogeochemical disturbance. In the case of northern peatlands drained by large and deep ditches, the rewetting effects are relatively unknown. The raised bog Grande plée Bleue (1,500 ha) is one of the largest pristine bogs in the St‐Lawrence lowlands in North America; however, it contained an old (>60 years), 750 m long, 3.5 m deep, and 8 m wide ditch. Rewetting of the area affected by the ditch was carried out by the construction of six dams at 40 cm elevation intervals and felling of all trees (with diameter at breast height >10 cm) within 30 m. Water table was restored to levels similar to intact bog reference sites, only at elevation differences up to 17 cm from the nearest lower dam, while rewetting did not affect pore‐water chemistry. Five to 6 years post‐rewetting, the cover of both pioneer mosses, and late successional mosses ( Sphagnum ) had not changed significantly compared with pre‐rewetting. This may have been due to the presence of dense shrub cover. For more effective ecohydrological restoration, dams should be spaced at smaller elevation intervals (e.g., every 20 cm of elevation or less), to allow recovery of water table along the entire length of the ditch, and vegetation introduction using the moss layer transfer technique may accelerate Sphagnum recruitment, especially in the few first metres from the ditch.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.620
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.224
Teacher spread0.203 · 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.

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

Citations13
Published2020
Admission routes1
Has abstractyes

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