Estimating Net Carbon and Greenhouse Gas Balances of Potato and Pea Crops on a Conventional Farm in Western Canada
Bibliographic record
Abstract
Abstract Quantifying the emissions of the three main biogenic greenhouse gases (GHGs), carbon dioxide (CO2), nitrous oxide (N2O) and methane (CH4), from agroecosystems is crucial. In this study continuous measurements of N2O, and CH4 emissions from potato and pea crops in southwest British Columbia, Canada were made using the eddy‐covariance (EC) technique. Flux footprint analysis, coupled with EC and manual nonsteady state chamber measurements, was used to address the spatial heterogeneity resulting from the field edge at the study site. Flux footprint corrections had a larger effect on N2O fluxes than CO2 fluxes because of a more pronounced difference in N2O fluxes between the crop and edge areas. After flux footprint corrections, the potato and pea crops were both weak CO2 sinks with annual net ecosystem exchange values of −57 ± 9 and −97 ± 16 g C m−2 yr−1, respectively. However, after taking carbon (C) export via crop harvest and C import via seeding into account, the potato crop shifted to being a moderate C source of 284 ± 55 g C m−2 yr−1, while the pea crop became near C neutral, sequestering only 30 ± 26 g C m−2 yr−1. Annual GHG balances, quantified by converting N2O and CH4 to CO2 equivalents as pulse emissions using respective global warming potentials on a 100‐year timescale, were 417 ± 88 and 152 ± 106 g CO2e m−2 yr−1 for the potato and pea crops, respectively, with N2O contributing the largest proportion to annual total GHG balances and outweighing the CO2 uptake from the atmosphere.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".