Two Bogs in the Canadian Hudson Bay Lowlands and a Temperate Bog Reveal Similar Annual Net Ecosystem Exchange of CO<sub>2</sub>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Two ombrotrophic bogs in Canada’s Hudson Bay Lowlands (HBL), an area storing an estimated 33 Gt of soil carbon, are contrasted with the Mer Bleue temperate ombrotrophic bog approximately 1000 km to the southeast to assess the net carbon dioxide (CO2) exchange between these ecosystems and the atmosphere. Peatlands in the HBL region may be impacted by not only climate change but also resource extraction practices that may cause drying of surrounding areas. Two years of eddy covariance CO2 flux measurements show the two HBL bogs to be annual sinks for CO2. Given random error and gap-filling uncertainties of 6 to 13 g C m-2 yr-1, the annual budgets of 45 to 55 g C m-2 yr-1 for the HBL bogs did not differ significantly from the temperate bog’s budget of 55 g C m-2 yr-1 (in the first year) despite differences in climate and vegetation composition and abundance. The temperate bog did have significantly greater net uptake of CO2 (78 g C m-2 yr-1) in the second study year. Component fluxes of photosynthesis and respiration were much smaller at the HBL bogs and speculated to be a result of less vascular vegetation. Less growing season CO2 uptake at the HBL bogs was offset by less winter loss when compared to the temperate bog. The influence of mid-summer drying and lowered water tables was similar among all three bogs. Decreasing mid-summer net ecosystem productivity (NEP) appeared to be a result of reduced photosynthetic uptake rather than increased respiration. In the short-term, drying of the HBL peatlands might result in a decrease of their C sink strength.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 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) | 0.000 | 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 it