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Record W3159969789 · doi:10.1139/cjb-2021-0035

Belowground morphology and population dynamics of two forest understory herbs of contrasting growth forms

2021· article· en· W3159969789 on OpenAlexaffvenue
Joseph A. Antos, Donald B. Zobel, Dylan G. Fischer

Bibliographic record

VenueBotany · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of Victoria
FundersOregon State UniversityU.S. Department of AgricultureU.S. Forest ServiceNational Science Foundation
KeywordsUnderstoryBiologyRhizomeCanopyRange (aeronautics)BotanyPopulationSeedlingEcology

Abstract

fetched live from OpenAlex

Forest understory herbs exhibit a large range of variation in morphology and life history. Here, we expand the reported range of variation by describing the belowground structures of two very different species, Xerophyllum tenax (Pursh) Nutt. and Chimaphila umbellata (L.) Nutt. We excavated individuals in forests of the Cascade Mountains in the Pacific Northwest of the United States. Xerophyllum tenax has short rhizomes but an extensive root system that is exceptionally large among forest understory species. The roots reach 4 m in length and may occupy an area 50 times that of the aboveground canopy. In contrast, C. umbellata has very small roots but an extensive rhizome system. The largest plant we excavated had 57 m of connected rhizomes and still had a seedling source. Both species have long-lived individuals but differ in response to disturbance. On the basis of monitoring 151 permanent 1 m2 plots in an old-growth forest, X. tenax increased only minimally in density over 40 years following tephra deposition from the 1980 eruption of Mount St. Helens, whereas the density of C. umbellata increased substantially. The very different morphology of these two species highlights the large range of variation found among forest herbs, which needs to be considered when examining the forest understory.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.010
GPT teacher head0.230
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2021
Admission routes2
Has abstractyes

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