Spatial variability of carbon emissions within a drained lake basin and its surrounding tundra, Illisarvik, Northwest Territories
Bibliographic record
Abstract
This study investigates the spatial and temporal variations of carbon emissions and their controls at a 38-year-old drained lake basin on Richards Island, NT.Greenhouse gas fluxes were collected from plots with different vegetation throughout the basin and in surrounding tundra during the growing season.Wet Sedge sites were significant sources of methane (7 to 355 nmol m -2 s -1 ) while most other sites were sinks.Carbon dioxide fluxes varied from 0.5 to 13 mol m -2 s -1 with highest fluxes outside the basin.Air temperature was positively correlated with carbon dioxide emissions at the majority of sites while soil moisture and vegetation type were the main controls on methane fluxes.Bulk age of the respired carbon dioxide was mostly modern, reflecting rapid cycling of recently sequestered carbon.Overall, carbon emissions were similar to those recorded at other tundra sites.This project could not have been possible without financial support of the Northern Scientific Training Program (NSTP), the Canadian Society for Agricultural and Forest Meteorology (CSAFM), the Ina Hutchison Award in Geography, Polar Continental Shelf Program grants to Chris Burn and Natural Science and Engineering Research Council of Canada Discovery grants to Elyn Humphreys and Chris Burn.I would like to thank Denis Granjon who positively influenced me and encouraged me to pursue this amazing field that is physical geography and Oliver Sonnentag who gave me the incredible opportunity to study abroad and who inspired me to pursue a Master's degree.I would also like to thank all my friends from Carleton grad studies for many good memories and for helping make the last two years incredible.Last but not least I am so grateful for my family and friends at home who showed me support throughout this journey, especially my parents who made this dream come true, merci.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".