Alternative method for estimating aboveground net primary productivity applied to balsam fir stands in eastern Canada
Bibliographic record
Abstract
Aboveground net primary productivity (ANPP) was measured in three balsam fir (Abies balsamea (L.) Mill.) forests on a climatic transect extending from southern New Brunswick ("warm" study area) to central Quebec ("cool" study area). Annual foliar production was estimated with a relationship between cross-sectional area at breast height of the current-year annual xylem ring and the mass of current-year foliage, using data obtained by harvesting trees at the beginning of the study. This relationship differed among study areas. Annual branch production was determined from annual foliar production and the ratio of annual branch production to annual foliar production. The ratio of branch to foliar production was estimated from intensive measurement of a sample of branches collected at the end of the study period; it varied among years but was similar for all study areas. ANPP was 3.36 Mg C·ha1·year1 at the warm study area, 3.73 Mg C·ha1· year1 at the mid-transect study area, and 3.04 Mg C·ha1·year1 at the cool study area. These estimates of ANPP were greater than those estimated using a conventional method of summing up increment and litterfall. On average, the conventional estimate of ANPP was 83% of the estimate using relationships described above. Because net ecosystem productivity is the difference between NPP and heterotrophic respiration, a 17% underestimate of NPP can have a substantial effect on the estimate of carbon-sink activity of a forest.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".