MétaCan
Menu
Back to cohort
Record W4409439793 · doi:10.1002/eco.70025

Mulching During Boreal Resource Development Alters Near‐Surface Hydrophysical Properties and Triggers Episodic Methane Emissions in Peatland Soils

2025· article· en· W4409439793 on OpenAlexafffundabout
Nicole Balliston, Marissa A. Davies, Koldobika Martín-Escudero, Maria Strack

Bibliographic record

VenueEcohydrology · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsUniversity of Waterloo
FundersEnvironment and Climate Change Canada
KeywordsPeatEnvironmental scienceBorealMethaneMulchSoil waterPermafrostHydrology (agriculture)Surface runoffResource (disambiguation)Soil scienceGeologyEcologyOceanography

Abstract

fetched live from OpenAlex

ABSTRACT Linear disturbances within boreal Canada (e.g. seismic lines) can significantly disrupt carbon cycling in northern peatlands, potentially transforming these significant carbon stocks from long‐term carbon sinks into net carbon sources. Recent efforts have been made to quantify the impacts of linear disturbance on vegetation, soil composition and greenhouse gas (GHG) emissions. However, little is known about the specific interactions between disturbances to peat hydrophysical structure and composition and the resulting alterations to CO 2 and CH 4 dynamics. To this end, eight poor fen peat cores were collected on, and eight cores collected adjacent to a seismic line representing the top 10 cm of the peat profile. These cores reflected four degrees of disturbance, with four cores per treatment: complete mulch covering, partial mulch covering, mechanical roughing only and undisturbed. In controlled laboratory conditions, cores were subjected to two subsequent static water table conditions (3 and 8 cm below the core surface) for ~30 days each with GHG flux measurements occurring every 2–3 days. Cores were then subdivided into 5 cm segments and underwent hydrophysical (i.e., bulk density, porosity and water retention) and compositional (i.e., C:N and vegetational assemblage) analysis. Results show that peat composition and hydrophysical structure were both strong predictors of GHG emissions. Higher CO 2 emissions were related to peat with high bulk density, low total and effective porosity and low C:N ratios, which occurred at depth in the undisturbed cores and at the surface where mechanical mulching and mixing occurred. Increased CH 4 emissions occurred in a subset of disturbed cores characterized by a reduction in macropores and effective porosity near the surface; these emissions were episodic and occurred where trapped gas was released. Further field‐scale research is needed to evaluate the interrelationships between the direct impacts of seismic line creation on hydrophysical structure and composition and the long‐term changes in carbon cycling within disturbed systems.

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 score0.047
Threshold uncertainty score0.670

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)0.0000.000

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 head0.009
GPT teacher head0.217
Teacher spread0.208 · 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 routes3
Has abstractyes

Explore more

Same venueEcohydrologySame topicPeatlands and Wetlands EcologyFrench-language works237,207