Spatial patterning of net primary production in wetlands of continental western Canada
Bibliographic record
Abstract
Net primary production in wetlands of continental western Canada (Alberta, Saskatchewan, Manitoba) is mapped and summarized by wetland type and ecoregion. The region contains 405 300 km2 of wetlands, with peatlands representing 90.1% of all wetlands. Based on a regional synthesis of published values of net primary production, shrubby swamp and marsh wetlands produce more biomass annually through the process of net primary production than peatlands. Different peatland types appear to sequester similar amounts of plant biomass on an annual basis, with the exception of permafrost bogs that sequester less. Wetland net primary production for the region is calculated as 2.1 ¥ 1014 g yr-1 of plant biomass, with 73.5% sequestered in peatlands. This is equivalent to 9.95 ¥ 1013 g yr-1 of carbon. Provincially this carbon is partitioned into 50% for Manitoba, 30% for Alberta, and 20% for Saskatchewan. Over the last 1000 years, an average of only 5% of this biomass (and carbon) accumulate as peat, with most lost through the process of decomposition. When the annual amount of carbon that accumulates as peat is compared to the amount emitted provincially as anthropogenic greenhouse gases, wetlands present in each of the provinces accumulate 4% (Alberta), 8% (Saskatchewan), and 62% (Manitoba) of the emitted carbon annually. Wetlands in continental western Canada are a significant, active biosphere carbon sink following accumulation patterns of the last one thousand years. Future changes, particularly in fire frequency or intensity, may alter this accumulation pattern.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| 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".