EFFECTS OF PLANT COMPENSATION ACROSS SITES ON REGRESSION ESTIMATES OF SHOOT BIOMASS AND LENGTH
Bibliographic record
Abstract
ABSTRACT: Regression estimates for determining browse shoot biomass from bite diameters and shoot basal diameters are commonly used to estimate biomass consumption and the impacts that her-bivores have on range resources. Such estimates tend to be based on equations built from data taken across the continuum of shoot morphometries present on plants within a given study area. How these morphometric relationships differ between the shoots of undamaged and damaged (e.g., following browsing, shoot breakage, or brush-cutting) plants is unclear. To assess the effects of plant compensa-tion and the importance of site on shoot morphometrics for Scouler's Willow (Salix scouleriana), we clipped and measured current annual shoots at 5 sites in central British Columbia. Each site had been previously brush-cut and current annual shoots were collected from both brush-cut and control willows. For each treatment and site, we developed separate regressions to predict shoot weight from length, weight from basal diameter, and length from basal diameter. Comparisons of individual regressions indicated that different regressions, or even different forms of regressions (i.e., power function versus linear), are needed to accurately predict shoot weight and length depending on whether or not plants are producing compensatory or non-compensatory shoots. For some willows in the same treatment category (brush-cut versus uncut), the appropriate regressions differed among some sites. These results suggest that the effects of plant compensation following mechanical damage have important implica-tions to the extrapolation and interpretation of shoot morphometric relationships, and thus, biomass estimates across different study areas. ALCES VOL. 44: 21-30 (2008)
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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 | 0.011 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".