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Climatic limits for the present distribution of beech (<i>Fagus</i> L.) species in the world

2006· article· en· W2109488328 on OpenAlexafffundabout
Jingyun Fang, Martin J. Lechowicz

Bibliographic record

VenueJournal of Biogeography · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaNational Science Foundation
KeywordsBeechDeciduousRange (aeronautics)Temperate climateTemperate deciduous forestSpecies distributionFagus sylvaticaEcologyGeographyEnvironmental sciencePhysical geographyBiologyHabitat

Abstract

fetched live from OpenAlex

Abstract Aim Beech (Fagus L., Fagaceae) species are representative trees of temperate deciduous broadleaf forests in the Northern Hemisphere. We focus on the distributional limits of beech species, in particular on identifying climatic factors associated with their present range limits. Location Beech species occur in East Asia, Europe and West Asia, and North America. We collated information on both the southern and northern range limits and the lower and upper elevational limits for beech species in each region. Methods In total, 292 lower/southern limit and 310 upper/northern limit sites with available climatic data for all 11 extant beech species were collected by reviewing the literature, and 13 climatic variables were estimated for each site from climate normals at nearby stations. We used principal components analysis (PCA) to detect climatic variables most strongly associated with the distribution of beech species and to compare the climatic spaces for the different beech species. Results Statistics for thermal and moisture climatic conditions at the lower/southern and upper/northern limits of all world beech species are presented. The first two PCA components accounted for 70% and 68% of the overall variance in lower/southern and upper/northern range limits, respectively. The first PCA axis represented a thermal gradient, and the second a moisture gradient associated with the world‐wide distribution pattern of beech species. Among thermal variables, growing season warmth was most important for beech distribution, but winter low temperature (coldness and mean temperature for the coldest month) and climatic continentality were also coupled with beech occurrence. The moisture gradient, indicated by precipitation and moisture indices, showed regional differences. American beech had the widest thermal range, Japanese beeches the most narrow; European beeches occurred in the driest climate, Japanese beeches the most humid. Climatic spaces for Chinese beech species were between those of American and European species. Main conclusions The distributional limits of beech species were primarily associated with thermal factors, but moisture regime also played a role. There were some regional differences in the climatic correlates of distribution. The growing season temperature regime was most important in explaining distribution of Chinese beeches, whilst their northward distribution was mainly limited by shortage of precipitation. In Japan, distribution limits of beech species were correlated with summer temperature, but the local dominance of beech was likely to be dependent on snowfall and winter low temperature. High summer temperature was probably a limiting factor for southward extension of American beech, while growing season warmth seemed critical for its northward distribution. Although the present distribution of beech species corresponded well to the contemporary climate in most areas, climatic factors could not account for some distributions, e. g., that of F. mexicana compared to its close relative F. grandifolia. It is likely that historical factors play a secondary role in determining the present distribution of beech species. The lack of F. grandifolia on the island of Newfoundland, Canada, may be due to inadequate growing season warmth. Similarly, the northerly distribution of beech in Britain has not reached its potential limit, perhaps due to insufficient time since deglaciation to expand its range.

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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.019
GPT teacher head0.237
Teacher spread0.218 · 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".

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Citations323
Published2006
Admission routes3
Has abstractyes

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