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Late‐glacial and Holocene palaeovegetation zonal reconstruction for central and north‐central North America

2005· article· en· W1931020451 on OpenAlexaffabout
Wayne L Strong, L. V. Hills

Bibliographic record

VenueJournal of Biogeography · 2005
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeology and Paleoclimatology Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsGeologyRadiocarbon datingHoloceneArcticPhysical geographyGlacial periodQuaternaryPollenTephraPaleontologyOceanographyEcologyGeographyVolcano

Abstract

fetched live from OpenAlex

Abstract Aim The purpose of this study is to develop palaeovegetation zonation models for central and north‐central North America, based on late‐Quaternary and Holocene pollen stratigraphic data ( n = 246 sites). A secondary purpose was to evaluate an hypothesis ( Strong & Hills, 2003 ) to explain the disjunct distribution of species in western Alberta. Location Hudson Bay‐Lake Michigan to the Rocky Mountains region, north of 36° N to the Arctic Ocean ( c. 70° N). Methods Pollen profiles spanning 40 years of palaeoecological research in North America were extracted from published and unpublished archival sources. Individual profiles were subdivided into 1000‐year increments based on the assumption of a constant sedimentation rate between stratigraphic dates (e.g. surface sediments, radiocarbon 14 C dates, tephra layers). The pollen composition among profiles was standardized to 54 commonly recognized taxa, with percentage composition within each stratigraphic sample prorated to 100% prior to analysis. Near‐surface sediments from these profiles were included as analogues of modern vegetation. Cluster analysis was used as a guide to the classification of 2356 temporal stratigraphic samples, which resulted in the recognition of 16 pollen groups. These groups were summarized in terms of their pollen composition, mapped, and used in combination with terrain information and an ecological knowledge of the study area to construct six physiognomically‐based palaeovegetation zonation models at 2000‐year intervals from 14,000 to 4000 yr bp (radiocarbon years before present). Results The 14,000 yr bp model placed Boreal and Cordilleran Forests proximal to the southern glacial front, whereas Arctic tundra dominated the Yukon Territory–Alaska ice‐free zone. Pollen and macrofossil evidence suggests that this Boreal Forest zone contained a mixture of coniferous and deciduous tree species. Grassland was postulated immediately south of the forest zone, with its northern extreme near 49° N latitude in the Alberta–Montana border area. Separation of the Laurentide and Cordilleran glacial fronts about 12,000 yr bp initiated the northward advance of Boreal Forests into western Canada. By the end of the Hypsithermal at about 6000 yr bp , Boreal Forests occurred near the Arctic Ocean, and Grassland and Aspen Parkland zones may have extended to 54° N and 59° N latitude in Alberta, respectively. Between 6000 and 4000 yr bp , a 5° and 1° latitudinal southward shift of the northern Boreal Forest and Grassland/Aspen Parkland boundaries occurred, respectively, near their contemporary positions with corresponding expansions of the Subarctic and Arctic zones. Modern Canadian Cordilleran Forests along the eastern slopes of the Rocky Mountains were interpreted as originating from the north‐central Montana–south‐western Alberta area. Jack pine ( Pinus banksiana Lamb.), a common Boreal Forest species, appears to have entered central Canada via the north side of Lake Superior after 11,000 yr bp . Main conclusions Modern vegetation in central Canada evolved from biomes located in the northern USA during the late‐Quaternary. The Boreal Forest biome contained the same arboreal taxa as the modern vegetation, except it lacked jack pine. The proposed regional palaeovegetation models support the hypothesis of Strong & Hills (2003) , but new independent palaeoecological data will be needed for a proper evaluation.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.316

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.010
GPT teacher head0.213
Teacher spread0.202 · 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

Citations63
Published2005
Admission routes2
Has abstractyes

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