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Record W2898028769 · doi:10.3390/f9100635

Whitebark Pine Prevalence and Ecological Function in Treeline Communities of the Greater Yellowstone Ecosystem, U.S.A.: Potential Disruption by White Pine Blister Rust

2018· article· en· W2898028769 on OpenAlexaboutno aff
Aaron C. Wagner, Diana F. Tomback, Lynn M. Resler

Bibliographic record

VenueForests · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
FundersUniversity of Colorado DenverNational Park ServiceU.S. Forest ServiceUniversity of Wyoming
KeywordsEcologyBiologyResistance (ecology)EcosystemRust (programming language)Disturbance (geology)

Abstract

fetched live from OpenAlex

In the northern Rocky Mountains of the U.S. and Canada, whitebark pine (Pinus albicaulis Engelm.) is a functionally important species in treeline communities. The introduced fungal pathogen Cronartium ribicola, which causes white pine blister rust, has led to extensive whitebark pine mortality nearly rangewide. We examined four treeline communities within the Greater Yellowstone Ecosystem (GYE) to assess structure and composition, whitebark pine prevalence and functional role, differences in growing season mesoclimate among study areas, and blister rust infection incidence. We found that (1) whitebark pine frequently serves as the majority overall, solitary, and leeward tree island conifer; (2) the prevalence of different tree species in the windward position in tree islands, and thus their potential as tree island initiators, may be predicted from their relative abundance as solitary trees; and (3) white pine blister rust infection incidence ranged from 0.6% to 18.0% across study areas. White pine blister rust poses a threat to treeline development and structure and the provision of ecosystem services in the GYE. Increasing blister rust resistance in nearby subalpine whitebark pine communities through seedling planting or direct seeding projects should eventually result in higher levels of blister rust resistance in whitebark pine in treeline 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score1.000

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)0.0010.000

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 head0.007
GPT teacher head0.208
Teacher spread0.201 · 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.

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

Citations7
Published2018
Admission routes1
Has abstractyes

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