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The biogeography of aquatic macrophytes in North America since the Last Glacial Maximum

2003· article· en· W2160885523 on OpenAlexafffund
Michael Sawada, André Viau, Konrad Gajewski

Bibliographic record

VenueJournal of Biogeography · 2003
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGlacial periodIce sheetBiogeographyLast Glacial MaximumRange (aeronautics)PollenMacrophyteWisconsin glaciationPhysical geographyTaxonIce ageOceanographyGeologyGeographyEcologyPaleontologySea iceIce streamCryosphereBiology

Abstract

fetched live from OpenAlex

Abstract Aim To document the post‐glacial migration of the major aquatic macrophytes of North America. Location North America north of Mexico. Methods Aquatic macrophyte pollen were extracted from the North American Pollen Database. The modern pollen distribution was mapped and related to the climate to document the geographical and climatic constraints on these taxa. The fossil pollen were mapped at 2‐ka intervals for the past 21 ka. Results Numerous genera were present in ice‐free Alaska during the Last Glacial Maximum, and south of the Laurentide Ice Sheet in the southeast. Those taxa with the widest modern climatic ranges migrated rapidly into ice‐marginal areas, first in the west and then in the east of North America. Subsequent changes in the range and abundance were smaller. Main conclusions There were four migration routes of aquatic macrophytes during the late‐glacial and post‐glacial periods: a southward migration from Alaska between 14–13 and ka, a northern migration in the west at the same time into the ice‐free Cordilleran region, and movements east and west of Appalachia as early as 19 ka for some taxa into the lower Mississippi and into the upper Mississippi and Great Lakes by 11 ka. As the Laurentide ice sheet wasted, aquatic taxa with the broadest contemporary temperature tolerances rapidly occupied ice‐marginal environments.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.793

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.009
GPT teacher head0.219
Teacher spread0.210 · 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 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

Citations44
Published2003
Admission routes2
Has abstractyes

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