The effects of bark quality on corticolous lichen community composition in urban parks of southern Ontario
Bibliographic record
Abstract
Tree bark characteristics influence lichen colonization. To better understand how urban parks can be managed to maximize lichen biodiversity, we examined trees in seven parks throughout the City of Guelph in southern Ontario. We measured bark characteristics and lichen communities on four common tree species that have a wide range of pH: Acer platanoides L., Acer × freemanii E. Murray, Pinus resinosa Aiton, and Pinus strobes L. We recorded the lichen species on 99 trees, calculated the pH and fissuring of the bark, and determined the diameter at breast height (DBH) as a proxy for age. Gamma diversity on all trees included 18 lichen taxa. We used graphite bark rubbings analyzed in ImageJ 1.47v to calculate the degree of bark fissuring. We collected bark samples from each tree trunk and determined the acidity with a pH meter. Using multivariate analyses we show that lichen community composition is positively correlated with DBH and tree species, but the degree of fissuring did not have a significant effect. We could not statistically analyze pH independent of tree species, but our results suggest pH is not a significant variable. We show lichen biodiversity in urban parks can be increased by planting a variety of tree species at different ages.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".