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Record W2997027054 · doi:10.1111/nph.16406

Determinants of geographic range size in plants

2020· review· en· W2997027054 on OpenAlexafffund
Seema N. Sheth, Naia Morueta‐Holme, Amy L. Angert

Bibliographic record

VenueNew Phytologist · 2020
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of British Columbia
FundersH2020 Marie Skłodowska-Curie ActionsNatural Sciences and Engineering Research Council of CanadaNational Research FoundationNational Institute of Food and AgricultureCenter for Makroøkologi, Evolution og KlimaDanmarks GrundforskningsfondU.S. Department of Agriculture
KeywordsBiological dispersalEcologyRange (aeronautics)MacroecologyBiologyNicheEvolutionary ecologyAdaptation (eye)Evolutionary biologyBiogeographyPopulation

Abstract

fetched live from OpenAlex

Geographic range size has long fascinated ecologists and evolutionary biologists, yet our understanding of the factors that cause variation in range size among species and across space remains limited. Not only does geographic range size inform decisions about the conservation and management of rare and nonindigenous species due to its relationship with extinction risk, rarity, and invasiveness, but it also provides insights into fundamental processes such as dispersal and adaptation. There are several features unique to plants (e.g. polyploidy, mating system, sessile habit) that may lead to distinct mechanisms explaining variation in range size. Here, we highlight key studies testing intrinsic and extrinsic hypotheses about geographic range size under contrasting scenarios where species' ranges are static or change over time. We then present results from a meta-analysis of the relative importance of commonly hypothesized determinants of range size in plants. We show that our ability to infer the relative importance of these determinants is limited, particularly for dispersal ability, mating system, ploidy, and environmental heterogeneity. We highlight avenues for future research that merge approaches from macroecology and evolutionary ecology to better understand how adaptation and dispersal interact to facilitate niche evolution and range expansion.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.957
Threshold uncertainty score0.598

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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)0.0000.000

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 head0.100
GPT teacher head0.290
Teacher spread0.190 · 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 designOther design
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

Citations155
Published2020
Admission routes2
Has abstractyes

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