Estimates of soil organic carbon stocks in central Canada using three different approaches
Bibliographic record
Abstract
This study compared three estimates of carbon (C) contained both in the surface layer (030 cm) and the total soil pools at polygon and regional scales and the spatial distribution in the three prairie provinces of western Canada (Alberta, Saskatchewan, and Manitoba). The soil C estimates were based on data from (i) analysis of pedon data from both the Boreal Forest Transect Case Study (BFTCS) area and from a national-scale soil profile database; (ii) the Canadian Soil Organic Carbon Database (CSOCD), which uses expert estimation based on soil characteristics; and (iii) model simulations with the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS2). At the polygon scale, good agreement was found between the CSOCD and pedon (the first method) total soil carbon values. Slightly higher total soil carbon values obtained from BFTCS averaged pedon data (the first method), as indicated by the slope of the regression line, may be related to micro- and meso-scale geomorphic and microclimate influences that are not accounted for in the CSOCD. Regional estimates of organic C from these three approaches for upland forest soils ranged from 1.4 to 7.7 kg C·m2 for the surface layer and 6.2 to 27.4 kg C·m2 for the total soil. In general, the CBM-CFS2 simulated higher soil C content compared with the field observed and CSOCD soil C estimates, but showed similar patterns in the total soil C content for the different regions. The higher soil C content simulated with CBM-CFS2 arises in part because the modelled results include forest floor detritus pool components (such as coarse woody debris, which account for 412% of the total soil pool in the region) that are not included in the other estimates. The comparison between the simulated values (the third method) and the values obtained from the two empirical approaches (the first two methods) provided an independent test of CBM-CFS2 soil simulations for upland forests soils. The CSOCD yielded significantly higher C content for peatland soils than for upland soils, ranging from 14.6 to 28 kg C·m2 for the surface layer and 60 to 181 kg C·m2 for the total peat soil depth. All three approaches indicated higher soil carbon content in the boreal zone than in other regions (subarctic, grassland).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".