Canopy macrolichen distribution in a very wet oldgrowth forest landscape of the upper Fraser River watershed.
Bibliographic record
Abstract
Windward slopes of the inland mountain ranges in British Columbia support a unique temperate rainforest ecosystem. Continued fragmentation and loss of old-growth forests in this globally rare ecosystem, has led to calls for the identification of conservation priorities between remaining stands. This thesis addresses this concern by surveying the relative abundances of 37 canopy macrolichens over a 70-km² area of remaining old-growth (>140 years) forest in the upper Fraser River watershed, British Columbia, Canada. To ensure adequate representation of landscape-scale old-growth forest characteristics, we divided study plots equally among leading tree species and between broadly defined sites of wet' and dry' relative soil moisture. Other variables included: minimum mean annual temperature, mean annual precipitation, solar loading, and canopy openness. This thesis integrates two statistical techniques: Nonmetric Multidimensional Scaling ordination for analysis of lichen assemblages and logistic regression to evaluate the habitat conditions of a subset of 8 lichen species previously identified as old-growth associated'. Ordination suggested that community assemblages were greatly influence by both the presence and abundance of bipartite cyanolichens. These communities correlated well with increasing levels of relative soil moisture, temperature, precipitation, and canopy openness, with little to no significant effect of tree leading species. Logistic regression models identified relative soil moisture and temperature in all parsimonious models. Leading tree species, in combination with moisture and temperature, were important factors explaining the presence or absence of 5 of 8 modeled lichen species. The results of this thesis emphasize the importance of maintaining representative areas of old-growth forests that are potentially less prone to natural disturbances such as fire. Of concern to the maintenance of lichen populations in old-growth inland temperate rainforests
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".