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Record W1842276873 · doi:10.3389/fpls.2015.00692

Biogeography of photoautotrophs in the high polar biome

2015· review· en· W1842276873 on OpenAlexaff
Stephen B. Pointing, Burkhard Büdel, Peter Convey, Len N. Gillman, Christian Körner, Sebastian Leuzinger, Warwick F. Vincent

Bibliographic record

VenueFrontiers in Plant Science · 2015
Typereview
Languageen
FieldEnvironmental Science
TopicPolar Research and Ecology
Canadian institutionsUniversité Laval
FundersNatural Environment Research CouncilSight Research UK
KeywordsBiomeBiogeographyBiologyBiological dispersalEcologyVascular plantBiodiversityArcticEcosystemMicroclimatePlant evolutionNiche

Abstract

fetched live from OpenAlex

The global latitudinal gradient in biodiversity weakens in the high polar biome and so an alternative explanation for distribution of Arctic and Antarctic photoautotrophs is required. Here we identify how temporal, microclimate and evolutionary drivers of biogeography are important, rather than the macroclimate features that drive plant diversity patterns elsewhere. High polar ecosystems are biologically unique, with a more central role for bryophytes, lichens and microbial photoautotrophs over that of vascular plants. Constraints on vascular plants arise mainly due to stature and ontogenetic barriers. Conversely non-vascular plant and microbial photoautotroph distribution is correlated with favorable microclimates and the capacity for poikilohydric dormancy. Contemporary distribution also depends on evolutionary history, with adaptive and dispersal traits as well as legacy influencing biogeography. We highlight the relevance of these findings to predicting future impacts on diversity of polar photoautotrophs and to the current status of plants in Arctic and Antarctic conservation policy frameworks.

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)0.004
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.921
Threshold uncertainty score0.827

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0030.000
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 head0.024
GPT teacher head0.284
Teacher spread0.260 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations67
Published2015
Admission routes1
Has abstractyes

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