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Record W2014775826 · doi:10.1139/x07-053

Effects of two silvicultural regimes with large tree retention on epiphytic macrolichen communities in Adirondack northern hardwoods, New York, USA

2007· article· en· W2014775826 on OpenAlexvenueno aff
Heather T. Root, Gregory G. McGee, Ralph D. Nyland

Bibliographic record

VenueCanadian Journal of Forest Research · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicLichen and fungal ecology
Canadian institutionsnot available
FundersNortheastern States Research CooperativeUniversity of VermontU.S. Department of Agriculture
KeywordsLichenEpiphyteGeographyEcologyForestryOld-growth forestBiology

Abstract

fetched live from OpenAlex

We sampled epiphytic lichen communities in nine Adirondack northern hardwood stands: three old growth, three reserve shelterwood, and three single-tree selection systems. Our objectives were to assess the effects of treatment, tree diameter at breast height, and their interaction on lichen communities and to determine whether lichen traits were associated with particular habitats. Lichen community composition was strongly related to tree diameter at breast height and differed between old growth and reserve shelterwoods. Lichen community composition was also related to an interaction between tree size and stand type. Lobaria pulmonaria (L.) Hoffm. was associated with large trees in old growth, whereas Evernia mesomorpha Nyl., Parmelia sulcata Taylor, and Physcia millegrana Degel. characterized those in shelterwood stands. Nitrophilous lichens were most common on small trees and in reserve shelterwoods, whereas small trees in selection systems and old growth supported lichens that were found to be most associated with larger trees overall. Selection systems apparently maintained lichen communities indistinguishable from those in old growth or reserve shelterwood. Because large trees hosted unique epiphyte assemblages particularly rich in fruticose and cyanolichen species, we expect that management retaining few or no large trees will alter epiphytic lichen communities.

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)0.000
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 score0.888
Threshold uncertainty score0.914

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.001
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 head0.050
GPT teacher head0.281
Teacher spread0.232 · 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
Published2007
Admission routes1
Has abstractyes

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