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Record W4315864459 · doi:10.1111/rec.13867

Terrestrial lichen caribou forage transplant success: year 5 and 6 results

2023· article· en· W4315864459 on OpenAlexafffundabout
Sean B. Rapai, Duncan McColl, Brianna Collis, Thomas Henry, Darwyn Coxson

Bibliographic record

VenueRestoration Ecology · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLichen and fungal ecology
Canadian institutionsGovernment of British ColumbiaPositive Living NorthUniversity of GuelphUniversity of Northern British Columbia
FundersFisheries and Oceans CanadaEnvironment and Climate Change CanadaBC Hydro
KeywordsLichenCladoniaWoodland caribouThreatened speciesHabitatVegetation (pathology)EcologySubarctic climateGeographyEnvironmental scienceBiologyForestry

Abstract

fetched live from OpenAlex

The southern mountain caribou—a subpopulation of caribou found in British Columbia—is listed on Schedule 1 of the Federal Species at Risk Act as Threatened. Woodland caribou are diet specialists, relying on Cladonia subgenus Cladina lichen as a primary food source during winter months. Lichens are burned along with trees and other vegetation during stand‐replacing wildfire events, a natural disturbance in caribou ranges. In an attempt to accelerate the return of post‐fire forests to productive caribou winter terrestrial lichen habitat, this study examined the survival and cover of three species of transplanted lichens in a post‐wildfire environment in north central British Columbia, Canada, both with and without forest litter amendments. Chlorophyll fluorescence was used to evaluate lichen survival by measuring potential photosynthetic activity. The results of this study demonstrate that transplanted fragments and mats of Cladonia subgenus Cladina had survived 5 and 6 years after being transplanted within a post‐wildfire environment, and had significantly greater percent cover when compared to the controls. The Fv/Fm results indicated that transplanted lichens survived, regardless of species, propagule type, or whether amendments were applied.

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 score0.288
Threshold uncertainty score0.543

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 head0.023
GPT teacher head0.235
Teacher spread0.212 · 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

Citations6
Published2023
Admission routes3
Has abstractyes

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