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Record W2917827280 · doi:10.1017/qua.2018.146

Postglacial wetland succession, carbon accumulation, and forest dynamics on the east coast of Vancouver Island, British Columbia, Canada

2019· article· en· W2917827280 on OpenAlexaffabout
Terri Lacourse, Kyle W. Beer, Kira Craig, Dante Canil

Bibliographic record

VenueQuaternary Research · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsHoloceneOmbrotrophicPeatGeologyBogWetlandMacrofossilMarshEcological successionPhysical geographyOceanographyTephraEcologyGeographyPaleontology

Abstract

fetched live from OpenAlex

ABSTRACT Peatland development and carbon accumulation on the Pacific coast of Canada have received little attention in paleoecological studies, despite wetlands being common landscape features. Here, we present a multi–proxy paleoenvironmental study of an ombrotrophic bog in coastal British Columbia. Following decreases in relative sea level, the wetland was isolated from marine waters by 13,300 cal yr BP. Peat composition, non-pollen palynomorph, and C and N analyses demonstrate terrestrialization from an oligotrophic lake to a marsh by 11,600 cal yr BP, followed by development of a poor fen, and then a drier ombrotrophic bog by 8700 cal yr BP. Maximum carbon accumulation occurred during the early Holocene fen stage, when seasonal differences in insolation were amplified. This highlights the importance of seasonality in constraining peatland carbon sequestration by enhancing productivity during summer and reducing decomposition during winter. Pollen analysis shows that Pinus contorta dominated regional forests by 14,000 cal yr BP. Warm and relatively dry summers in the early Holocene allowed Pseudotsuga menziesii to dominate lowland forests 11,200–7000 cal yr BP. Tsuga heterophylla and P. menziesii formed coniferous forest in the mid- and late Holocene. Tephra matching the mid-Holocene Glacier Peak–Dusty Creek assemblage provides evidence of its most northwesterly occurrence to date.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.067
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.262
Teacher spread0.244 · 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.

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

Citations10
Published2019
Admission routes2
Has abstractyes

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