Advantages of long-term measurement of fine root demographics with a minirhizotron at two balsam fir sites
Bibliographic record
Abstract
We used 15 site-years of minirhizotron observations (1998–2006 at one site; 1998–2000 and 2004–2006 at second site) from two mature balsam fir ( Abies balsamea (L.) Mill.) sites to quantify interannual variability in fine root demography and assess the accuracy of estimates from early years of observation. Annual production varied fourfold at Forêt Montmorency (FM) (5.8–26.5 roots·100 cm–2) and twofold at Green River (GR) (7.2–14.2 roots·100 cm–2). Annual mortality varied more than 30-fold at the two sites (FM: 0.7–23.2 roots·100 cm–2; GR: 0.3–10.9 roots·100 cm–2), year-end standing crops varied two- to eight-fold (FM: 3.6–28.4 roots·100 cm–2; GR 8.5–18.6 roots·100 cm–2), and median life-span of annual cohorts varied from 180 to 540 days at FM and from 350 to 577 days at GR. This variation illustrates that root demography estimates from short-term studies may differ widely from long-term means. Annual mortality and standing crops were lowest in the first year of observation and tended to increase for two or more years at both sites, whereas these trends were not observed for annual production. Our results indicate that minirhizotron tubes must be in place for more than 2 years to accurately estimate fine root demography at balsam fir sites.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".