1 TCP Progress Report and Renewal Proposal: Measuring the Effects of Stand Age and Soil Drainage on Boreal Forest Net Ecosystem Production
Bibliographic record
Abstract
We request support to continue investigating the exchange of CO2 between the atmosphere and the boreal forest in Manitoba, Canada. During the last two years we have used year-round eddy covariance and associated ecological measurements to study the effects of forest age on forest-atmosphere CO2 exchange. During the next three years we plan to: (1) complete our study of the effect of stand age on CO2 exchange by collecting 18 more months of data at six sites that differ in time since burn from 4 years to 150 years, and (2) begin investigating the effect of soil drainage on carbon balance. Our work to date has yielded several major payoffs for DOE’s TCP Program. We have (1) designed, tested, and demonstrated a lightweight, fully portable eddy flux system that will allow relatively inexpensive year-round measurements of CO2 exchange at almost any micrometeorologically-suitable site, (2) added six year-round sites to AmeriFlux, at a relatively low per site cost, and (3a) developed a partial understanding of how and why ecosystem carbon balance changes as forests age. Our work during the next three years will add to this list of payoffs. We will (3b) develop a much more complete understanding of how and why ecosystem carbon balance changes as forests age, and (4) develop an understanding of how soil drainage affects NEP, and how the carbon balance of poorly-drained sites compares with that of nearby well drained sites. All of these issues have been identified by the US Global Carbon Cycle Plan and the North American Carbon Cycle Plan as problems or approaches that merit priority attention. 2
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.
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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".