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Record W2107242411 · doi:10.2980/15-4-3154

Influences of tree age and tree structure on the macrolichen <i>Letharia vulpina</i>: A case study in the Italian Alps

2008· article· en· W2107242411 on OpenAlexvenueno aff
Juri Nascimbene, Lorenzo Marini, Marco Carrer, Renzo Motta, Pier Luigi Nimis

Bibliographic record

VenueEcoscience · 2008
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLichen and fungal ecology
Canadian institutionsnot available
Fundersnot available
KeywordsTree (set theory)LichenLarchEcologyForest managementPropaguleEpiphyteBiological dispersalForestryGeographyMathematicsBiologyDemographyPopulation

Abstract

fetched live from OpenAlex

Tree age and tree structure are important determinants for epiphytic lichen communities, affecting substrate stability, light availability, and propagule dispersal. However, little is known about the relative importance of these 2 factors on many species. This work aims to evaluate the importance of tree age and tree structure in explaining the within-stand frequency of the macrolichen Letharia vulpina. The study was carried out in 2 larch-stone pine forests in the Eastern Italian Alps. The frequency of Letharia was evaluated using a standard sampling method. To explain the within-stand frequency of Letharia, tree age and several variables related to tree structure were considered. Multiple ordinary least square regression was applied to clarify the influence of the set of variables. Several partial regressions were then computed to evaluate the relative importance of each significant predictor. The frequency of Letharia increases with increasing tree age, tree diameter, and first branch height. Tree age is the most important variable, accounting for one third of the total explained variation, although tree structure also has a significant effect on lichen frequency. Due to its dispersal limitations and old-tree dependence Letharia is proposed as a suitable indicator of forest continuity. The results may be of interest for conservation purposes, since the frequency of Letharia may be enhanced by protecting old trees.

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 score0.096
Threshold uncertainty score0.962

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.039
GPT teacher head0.245
Teacher spread0.206 · 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

Citations16
Published2008
Admission routes1
Has abstractyes

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