Estimating carbon stocks and stock changes in Interior Wetbelt forests of British Columbia, Canada
Bibliographic record
Abstract
Abstract The Interior Wetbelt (IWB) of British Columbia includes the globally rare Inland Temperate Rainforest (ITR) that if managed for its substantial carbon (C) stocks can contribute to Canada's Nationally Determined Commitment under the Paris Climate Agreement. We provide spatially explicit estimates of above‐ and belowground live and dead biomass and soil C stocks derived from three sources: (1) government online Vegetation Resources Inventory (VRI); (2) the GlobBiomass spatial dataset; and (3) field plots ( n = 27) within old‐growth forests of the ITR. For live aboveground C, we summarize C stocks by elevation classes and decadal forest age. The upper bound on total C densities (above‐ and belowground live and dead biomass and soil C) based on VRI was a maximum of 806 megagrams (Mg) C ha −1 . The mean total biomass C density measured in field plots was 583 Mg C ha −1 with a maximum of 1275 Mg C ha −1 , which is on par with some of the world's most C‐dense temperate forests. About half the C is in live biomass pools with the rest in dead biomass and soil organic C pools. The mean C density from the VRI over all elevations was 182 Mg C ha −1 , with soil organic C ~40% and live tree stems ~27%. Vegetation Resources Inventory estimates were 75% lower than field‐based measurements with the greatest mismatch in areas with the highest C density. Approximately 22% of the IWB has been logged, the majority since 1970s, resulting in live above ground C declining by at least 18%, although this is likely an underestimate. Logging was heavily concentrated in low (<1000 m; 28.3% of elevation zone) to mid‐elevations (1000–2000 m; 20.9%) compared with upper elevations (>2000 m; 1.2%). The region contains underappreciated C stocks that can help Canada meet its climate and conservation targets, but only if there are major forestry reforms that protect C‐dense old‐growth forests, allow degraded forests time to recover the logging‐related C debt, and improve monitoring of C stocks and stock changes.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".