Soil CO2 and CH4 effluxes in powerline rights-of-way and their adjacent forests
Bibliographic record
Abstract
Global decarbonization will require a large deployment of power grids to convey electricity. The right-of-way (i.e., the cleared area below the pylons, where vegetation is periodically maintained) is a land-use change that involves changes in soil and vegetation and their carbon dynamics both within the rights-of-way and in adjacent forests, notably via an edge effect. Our main objective was to assess whether soil CO 2 effluxes (F CO 2 ), soil CH 4 effluxes and microclimate (soil temperature and water content) differed between powerline rights-of-way and their adjacent forests compared to control forests over a large bioclimatic gradient of upland sites across the temperate and boreal forests of Eastern Canada. Monthly efflux measurements were carried out between May and October 2023 and 2024 in eight rights-of-way and their adjacent edge and control forests. Overall, cumulative total F CO 2 during the snow-free period were lower (–7.57 %) in rights-of-way and higher (+11.20 %) in the edge forests compared to the control forests. However, these results were not consistent across the bioclimatic gradient: balsam fir forests, contrarily to forests from both cooler and warmer bioclimatic domains, showed enhanced soil respiration in rights-of-way. Overall, soils were warmer and wetter in rights-of-way compared to control and edge forests; however, no effects were found on the soil methane uptake. Our study indicated that the presence of a powerline right-of-way influences soil biogenic carbon emissions. Effects are related both to changes in abiotic and biotic conditions. These estimates should improve the assessment of the carbon footprint of power transmission and electricity deployment.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".