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Record W1813883602 · doi:10.1139/cjfr-2013-0024

Habitat loss exceeds habitat regeneration for an IUCN flagship lichen epiphyte: <i>Erioderma pedicellatum</i>

2013· article· en· W1813883602 on OpenAlexaffvenue
Robert P. Cameron, Ian Goudie, D. H. S. Richardson

Bibliographic record

VenueCanadian Journal of Forest Research · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLichen and fungal ecology
Canadian institutionsSaint Mary's UniversityGolder Associates (Canada)Nova Scotia Department of EnergyTechnical University of Nova Scotia
Fundersnot available
KeywordsHabitatBorealEndangered speciesTaigaThreatened speciesIUCN Red ListEnvironmental scienceEcologyLichenHabitat destructionCritical habitatForestryGeographyBiology

Abstract

fetched live from OpenAlex

The boreal felt lichen (Erioderma pedicellatum (Hue) P.M. Jørg.) is globally critically endangered, being threatened by forestry operations, habitat disturbance, and air pollution. To determine if loss of habitat due to forestry activities has occurred in Nova Scotia, a predictive habitat model was built using historical data from 1988. Satellite data were used for the period between 1987 and 2005 to determine the amount of suitable habitat harvested during this period. Available habitat was modeled through time from 1988 to 2005 in which area harvested was subtracted and regeneration was added in 3- to 5-year time steps. The predicted suitable boreal felt lichen habitat area was then modeled from 2005 to 2055 using the same harvesting assumptions and modeling process, but using 10-year time steps. The results of the model indicated that there has been a loss of 2311 ha (11.5%) in the amount of predicted suitable boreal felt lichen habitat between 1988 and 2005. A forward-projected drop is predicted between 2005 and 2055 that will amount to 4499 ha (25.4%), assuming no change in forest harvesting. Protection of unoccupied habitat surrounding existing boreal felt is recommended.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.600
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.066
GPT teacher head0.293
Teacher spread0.228 · 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

Citations15
Published2013
Admission routes2
Has abstractyes

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