The influence of regional gradients in climate and air pollution on epiphytes in riparian forest galleries of the upper Fraser River watershed
Bibliographic record
Abstract
Epiphyte diversity and abundance were examined along the Fraser River and its tributaries in central-interior British Columbia at varying distances from point-source air pollution discharges. Black cottonwood (Populus balsamifera L. ssp. trichocarpa (Torr. & A. Gray ex Hook.) Brayshaw trunks near discharges in Prince George had comparatively low epiphyte diversity and supported an unusual acidiphilic lichen community, including Tuckermannopsis chlorophylla (Willd.) Hale, Usnea lapponica Vain., and Vulpicida canadensis (Räsänen) J.-E. Mattsson & M.J. Lai. At a greater distance from air pollution sources, a more characteristic flora was observed, including Collema Wigg. spp., Lecidea erythrophaea Flörke, Leptogium (Ach.) Gray spp., Lobaria pulmonaria (L.) Hoffm., Nephroma parile (Ach.) Ach., Peltigera Willd. spp., and Strangospora moriformis (Ach.) Stein. These changes were accompanied by large differences in bark pH; mean values ranged from 3.7 in Prince George to 6.7 in upriver stands for black cottonwoods, from 3.5 to 5.4 for live spruce branches (Picea glauca (Moench) Voss), and from 3.1 to 4.9 for dead spruce branches, respectively. Epiphyte communities proximal to Prince George were characterized by many nitrophilous species. Our data showed a strong covariate influence of climate, with Lobarion community lichens more abundant in the easternmost high-precipitation plots. Numerous provincial- and global-level conservation priority species were found, including Collema quadrifidum D.F. Stone & McCune, newly discovered for Canada; Collema coniophilum Goward, a Species at Risk Act listed species; and provincially at risk Heterodermia speciosa (Wulf.) Trev., Physcia tribacia (Ach.) Nyl., and Santessoniella saximontana T. Sprib., P.M. Jørg. & M. Schultz, mostly in sites distant from air pollution sources.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".