Estimating Lichenometric Ages by Direct and Indirect Measurement of Radial Growth: A Case Study of Rhizocarpon agg. at the Illecillewaet Glacier, British Columbia
Bibliographic record
Abstract
Data for Rhizocarpon agg. thalli at the Illecillewaet Glacier in British Columbia were used to see whether a single growth curve could provide accurate age estimates on either side of the Continental Divide, to determine whether modern and historical growth rates are similar, and to test a published model that estimates lichen age from short-term radial growth rates. A lichen growth curve was developed for Rhizocarpon agg. using thallus-size data from 14 tree-ring and historically dated substrates. Comparison of this curve with one developed on similar materials 250 km north of this location found similar growth rates for the first 150 yr but slightly faster growth over the next 150 yr at the Illecillewaet site. Radial growth was also measured annually at an average of five points at 105 Rhizocarpon agg. thalli to see if direct-measurement data could be used to reliably estimate lichenometric ages. Radial growth from 1996–2000 ranged between 0.262 and 0.412 mm yr−1and showed large variation within and between thalli. Mathematical analysis found that radial growth was not a positive function of the radius, and linear regression incorrectly predicted that growth rates increase with thallus size. Ages estimated by linear extrapolation of the 4-yr mean growth rate were ca. 10 yr less than those estimated by the indirectly calibrated growth curve on surfaces <200 yr old. Progressively less accurate minimum estimates were obtained using linear extrapolation of radial growth rates for old surfaces and thalli >60-mm diameter. These findings lend support to the assumption that modern growth rates of Rhizocarpon lichens averaged over several years can potentially provide close estimates of lichenometric age.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".