CO2 Soil Flux in Temperate Forests Located in Southern Ontario
Bibliographic record
Abstract
Forests sequester large amounts of CO2 from the atmosphere, playing a significant role in the global carbon cycle and contributing significantly to building carbon sinks. Some of the sequestered carbon is released back into the atmosphere through autotrophic and heterotrophic respiration. The release of carbon, known as soil respiration (Rs), is regulated by environmental factors, primarily soil temperature (Ts) and soil moisture (SM). This study examines the difference in Rs at two forests sites in Southern Ontario for the 2021 growing season using automated CO2 flux measurement systems. The first site is a mature coniferous forest (TP74), and the second is a mature deciduous forest (TPD). There was no clear relationship between Rs and Ts or SM at both sites, primarily due to limited observed data available in 2021. However, it was found that an increase in SM could cause a different Rs response between the sites. When both sites experienced an increase in SM, on the same day, Rs increased at TPD, but Rs decreased at TP74. The difference in the response may be due to differences in organic material between sites, with TPD having a higher amount of organic material. A Rs Ts SM model was fitted to the data, but the correlation was poor at both sites. Model parameters from a past study at TPD were used to simulate Rs at TPD for whole year. These findings contribute to the understanding of Rs in different forest types and how environmental factors may alter rates of Rs.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".