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Little change in the fir tree‐line position on the southeastern Tibetan Plateau after 200 years of warming

2011· article· en· W2139995297 on OpenAlexfundno aff
Eryuan Liang, Yafeng Wang, Dieter Eckstein, Tianxiang Luo

Bibliographic record

VenueNew Phytologist · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
FundersNational Key Research and Development Program of ChinaUniversity of British ColumbiaNational Natural Science Foundation of ChinaChinese Academy of SciencesNational Science Foundation
KeywordsEcotonePlateau (mathematics)Tree lineClimate changeGlobal warmingDendrochronologyLine (geometry)Douglas firEcologyGeographyBiologyForestryMathematicsHabitat

Abstract

fetched live from OpenAlex

• As one of the world's highest natural tree lines, the Smith fir (Abies georgei var. smithii) tree line on the southeastern Tibetan Plateau is expected to vary as a function of climate warming. However, the spatial patterns and dynamics of the Smith fir tree line are not yet well understood. • Three rectangular plots (30 m × 150 m) were established in the natural alpine tree-line ecotone on two north-facing (Plot N1, 4390 m asl; Plot N2, 4380 m asl) and one east-facing (Plot E1, 4360 m asl) slope. Dendroecological methods were used to monitor the tree-line patterns and dynamics over a 50-yr interval. • The three study plots showed a similar pattern of regeneration dynamics, characterized by increased recruitment after the 1950s and an abrupt increase in the 1970s. Smith fir recruitment was significantly positively correlated with both summer and winter temperatures. However, Smith fir tree lines do not show a significant upward movement, despite warming on the Tibetan Plateau. • The warming in the past 200 yr is already having a significant impact on the population density of the trees, but not on the position of the Smith fir tree line.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.069
GPT teacher head0.258
Teacher spread0.189 · 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 source (direct Gemma or distilled Codex), 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

Citations208
Published2011
Admission routes1
Has abstractyes

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