Table1_Soil CO2 Emission Largely Dominates the Total Ecosystem CO2 Emission at Canadian Boreal Forest.DOCX
Bibliographic record
Abstract
<p>The natural carbon dioxide (CO<sub>2</sub>) emission from the ecosystem, also termed as the ecosystem respiration (R<sub>eco</sub>), is the primary natural source of atmospheric CO<sub>2</sub>. The contemporary models rely on empirical functions to represent decomposition of litter with multiple soil carbon pools decaying at different rates in estimating R<sub>eco</sub> variations and its partitioning into autotrophic (R<sub>a</sub>) (originating from plants) and heterotrophic (originating mostly from microorganisms) respiration (R<sub>h</sub>) in relation to variation in temperature and soil water content. Microbially-mediated litter decomposition scheme representation are not very popular yet. However, microbial enzymatic processes play integral role in litter as well as soil organic matter (SOM) decomposition. Here we developed a mechanistic model comprising of multiple hydro-biogeochemical modules in the soil and water assessment tool (SWAT) code to explicitly incorporate microbial-enzymatic litter decomposition and decomposition of SOM for separately estimating regional-scale R<sub>a</sub>, R<sub>h</sub> and R<sub>eco</sub>. Modeled annual mean R<sub>eco</sub> values are found varying from 1,600 to 8,200 kg C ha<sup>−1</sup> yr<sup>−1</sup> in 2000–2013 within the boreal forest covered sub-basins of the Athabasca River Basin (ARB), Canada. While, for the 2000–2013 period, the annual mean R<sub>a</sub>, R<sub>h</sub> and soil CO<sub>2</sub> emission (R<sub>s</sub>) are varying within 800–6,000 kg C ha<sup>−1</sup> yr<sup>−1</sup>, 700–4,200 kg C ha<sup>−1</sup> yr<sup>−1</sup> and 1,200–5,000 kg C ha<sup>−1</sup> yr<sup>−1</sup>, respectively. R<sub>s</sub> generally dominates R<sub>eco</sub> with nearly 60–90% contribution in most of the sub-basins in ARB. The model estimates corroborate well with the site-scale and satellite-based estimates reported at similar land use and climatic regions. Mechanistic modeling of R<sub>eco</sub> and its components are critical to understanding future climate change feedbacks and to help reduce uncertainties particularly in the boreal and subarctic regions that has huge soil carbon store.</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.888 | 0.002 |
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; both teacher heads agree on what is shown here.
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".