Spatially simulating changes of soil water content and their effects on carbon sequestration in Canada’s forests and wetlands
Bibliographic record
Abstract
The variations of soil water content (SWC) and its influences on the carbon (C) cycle in Canada’s forests and wetlands were studied through model simulations using the Integrated Terrestrial Ecosystem Carbon (InTEC) model. It shows that Canada’s forests and wetlands experienced spatially and temporally heterogeneous changes in SWC from 1901 to 2000. SWC changes caused average NPP to decrease 40.8 Tg C yr−1 from 1901 to 2000, whereas the integrated effect of non-disturbance factors (climate change, CO2 fertilization and N deposition) enhanced NPP by 9.9%. During 1981–2000, the reduction of NPP caused by changes in SWC was 58.1 Tg C yr−1 whereas non-disturbance factors together caused NPP to increase by 16.6%. SWC changes resulted in an average increase of 4.1 Tg C yr−1 in the net C uptake during 1901–2000, relatively small compared with the enhancement in C uptake of 50.2 Tg C yr−1 by the integrated effect of non-disturbance factors. During 1981–2000, changes in SWC caused a reduction of 3.8 Tg C yr−1 in net C sequestration whereas the integrated factors increased net C sequestration by 54.1 Tg C yr−1. Increase in SWC enhanced C sequestration in all ecozones.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".