Assessing Peatland Law and Policy Across Canada: Is Canada Fulfilling Its Critical Stewardship Role?
Bibliographic record
Abstract
Peatlands are freshwater wetland ecosystems defined by large deposits of decaying plant material (peat soils).Peatlands provide a unique and essential service: cooling the global climate by slowly removing CO 2 from the atmosphere over thousands of years and storing this carbon in deep peat soils (Frolking and Roulet 2007;Harris et al. 2021).Peatlands now store approximately 30% of Earth's soil carbon on just 3% of the land surface (Xu et al. 2018;Hugelius et al. 2020).This is more carbon than all the trees on the planet.Canada plays a critical role in global peatland stewardship.Canada contains roughly one-quarter of the world's peatlands, including some of the world's largest remaining intact peatland complexes.The Hudson Bay Lowland, which spans Ontario and crosses over into Manitoba (with portions in Quebec), and the Mackenzie River Basin, which is located primarily in the Northwest Territories (with portions in the Yukon, British Columbia and Alberta), are two of the largest peatland complexes in the world.Peatlands in Canada store approximately 28% of the global peatland carbon stock (Tarnocai et al 2011; Hugelius and others 2020), making them natural climate solutions of global importance.Of all provinces and territories, Ontario contains the largest peat carbon stock, followed by Manitoba and the Northwest Territories (Map 1).Below: Map 1 -Canada Peatland Carbon Stock Canada's critical role in peatland stewardship 1. WCS Canada analysis using the Hugelius peatland dataset, "Maps of northern peatland extent, depth, carbon storage and nitrogen storage" (Hugelius et al 2020).2. The National Peatland Policy Project is a collaborative project led by WCS Canada that aims to inform future government policy related to peatlands in Canada.Learn more at our project website.
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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 | 0.009 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".