Can age be predicted from diameter for the obligate seeder Allocasuarina littoralis (Casuarinaceae) by using dendrochronological techniques?
Bibliographic record
Abstract
In fire-prone regions, assessing stand age of obligate-seeding species provides an estimate of time since last fire. If a relationship exists between tree age and diameter, measuring the stem diameter of trees is a simple field method for determining age-class distribution within a stand. In this study, we examined whether age of the obligate seeder Allocasuarina littoralis could be estimated from diameter by using dendrochronological applications. Analysis of radial samples established that A. littoralis puts down annual growth rings. The relationship between the number of growth rings and stem diameter was tested for both male and female stems by using regression analysis. For female plants, this relationship varied significantly between sites. In contrast, male stems provided a strong relationship between age (as a function of the number of growth rings) and diameter, regardless of site. A regression model estimating age from stem diameter, based on male trees only, was subsequently developed and tested with data collected from trees of known age. Predicted estimates from stem diameter were within 3.76 years of the true age. Field measures of stem diameters can therefore provide a tool for estimating the fire history, especially time since last fire, in areas where stands of this species occur.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".