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Lichenological evidence for the recognition of inland rain forests in western North America

2005· article· en· W2117793462 on OpenAlexafffund
Trevor Goward, Toby Spribille

Bibliographic record

VenueJournal of Biogeography · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLichen and fungal ecology
Canadian institutionsUniversity of British Columbia
FundersYellowstone to Yukon Conservation InitiativeU.S. Forest ServiceParks CanadaWilburforce Foundation
KeywordsRainforestTemperate rainforestGeographySpecies richnessTemperate climateEcologyEpiphyteBiomeTemperate forestEcosystemBiology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.170
Threshold uncertainty score0.104

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.055
GPT teacher head0.270
Teacher spread0.215 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations58
Published2005
Admission routes2
Has abstractyes

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