Lichenological evidence for the recognition of inland rain forests in western North America
Bibliographic record
Abstract
Abstract Aim The coastal temperate rain forests of north‐western North America are internationally renowned as the archetypal expression of the temperate rain forest biome. Less well documented is the existence of somewhat similar forests 500–700 km inland on the windward slopes of the Columbia and Rocky Mountains. Here we attempt to show that these inland ‘wetbelt’ forests warrant rain forest status. Location North‐western North America. Methods We use tree‐dwelling macrolichens to assess the degree of environmental congruence between the coastal temperate rain forests and their inland counterparts. Results We report three key findings: (1) 40% of oceanic, epiphytic macrolichens found in Pacific coastal rain forests occur also in inland regions; (2) epiphytic species richness decreases with decreasing latitude, such that roughly 70% of disjunct oceanic species are restricted to regions north of 51° N; and (3) the southward decline in lichen diversity is correlated with a parallel decrease in summer precipitation, but not with mean annual precipitation. Main conclusions These observations are consistent with the recognition of an inland rain forest formation between 50 and 54° N. Inland rain forests represent a small, biologically significant ecosystem whose continued fragmentation and conversion to tree plantations warrant close scrutiny.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".