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Record W2066104535 · doi:10.1139/b10-066

Different factors govern the performance of three closely related and ecologically similar<i>Dryopteris</i>species with contrastingly different abundance in a transplant experiment

2010· article· en· W2066104535 on OpenAlexvenueno aff
Kai Rünk, Martin Zobel, Kristjan Zobel

Bibliographic record

VenueBotany · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFern and Epiphyte Biology
Canadian institutionsnot available
FundersEuropean Regional Development FundEesti MaaülikoolEesti TeadusfondiTartu ÜlikoolEuropean Commission
KeywordsDryopterisEdaphicBiologySporophyteAbundance (ecology)EcologyPteridophyteBiological dispersalHabitatBotanyRare speciesFernSoil waterPopulation

Abstract

fetched live from OpenAlex

We conducted a transplant experiment to address aspects of the contrasting ecological performance of three forest ferns with similar habitat preferences: Dryopteris carthusiana (Vill.) H.P. Fuchs (common in Estonia), Dryopteris expansa (C. Presl) Fraser-Jenkins &amp; Jermy (less common in Estonia), and Dryopteris dilatata (Hoffm.) A. Gray (rare in Estonia). Sporophytes of the three species were reciprocally planted in pots of soil in three neighbouring sites, where only (i) the most common, (ii) two more common, or (iii) all three grow naturally. The experimental design allowed the grouping of the possible limiting factors: light-related, soil-related, and effect of locale (factors associated with a particular locality but not directly related to light or soil). D. expansa (less common) was vulnerable to edaphic conditions: its performance was significantly poorer in soil from the site where it was naturally absent. D. dilatata (rare) was unaffected by soil conditions, indicating that either limited dispersal or effect of locale is responsible for its rarity. Our results indicate that even for taxonomically close and ecologically similar species, the forces that shape plants’ distribution and abundance can be markedly different.

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 score0.427
Threshold uncertainty score0.444

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 head0.012
GPT teacher head0.181
Teacher spread0.169 · 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

Citations8
Published2010
Admission routes1
Has abstractyes

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