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Record W7161999948 · doi:10.82308/6501

Environmental niche partitioning among riparian sedges (Carex, Cyperaceae) in the St. Lawrence Valley, Quebec

2007· dissertation· en· W7161999948 on OpenAlexaboutno aff
Laura. Plourde

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicBotany, Ecology, and Taxonomy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsNicheDiaspore (botany)CarexNiche differentiationRiparian zoneEcological nicheEnvironmental gradientWetland

Abstract

fetched live from OpenAlex

To understand maintenance of the within-habitat diversity of closely related species, I investigated 11 Carex species growing along rivers in the south-western St. Lawrence Valley of Quebec. Microenvironments within a half meter of focal plants characterized for Carex comosa, C. crinita, C. grayi, C. intumescens, C. lacustris, C. lupulina, C. pseudocyperus, C. retrorsa, C. tuckermanii, C. typhina, and C. vesicaria revealed significant differences among the species in their environmental affinities. Species appear to fall into groups based on their tolerance of flooding and are secondarily differentiated on other environmental gradients such as insolation, soil pH and soil organic matter. Several traits were related to the environments that species inhabit: diaspore weight, diaspore floating duration, and root aerenchyma. The absence of any phylogenetic trend in niche differences for pairs of species supports the idea that evolutionary differentiation of the alpha-niche is the basis for coexistence of congeners.

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 score0.058
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.022
GPT teacher head0.237
Teacher spread0.215 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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