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Are hybrid species more fit than ancestral parent species in the current hybrid species habitats?

2010· article· en· W2151849021 on OpenAlexaff
Lisa A. Donovan, David M. Rosenthal, M. SANCHEZ‐VELENOSI, Loren H. Rieseberg, Fulco Ludwig

Bibliographic record

VenueJournal of Evolutionary Biology · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of British ColumbiaCanadian Institute for Health Information
FundersNational Institute of General Medical SciencesUtah State UniversityNational Institutes of HealthNational Science Foundation
KeywordsBiologyHabitatHybridGenetic algorithmAdaptation (eye)EcologyHybrid zoneEcological speciationTaxonIncipient speciationGene flowGenetic variationBotany

Abstract

fetched live from OpenAlex

Hybrid speciation is thought to be facilitated by escape of early generation hybrids into new habitats, subsequent environmental selection and adaptation. Here, we ask whether two homoploid hybrid plant species (Helianthus anomalus, H. deserticola) diverged sufficiently from their ancestral parent species (H. annuus, H. petiolaris) during hybrid speciation so that they are more fit than the parent species in hybrid species habitats. Hybrid and parental species were reciprocally transplanted into hybrid and parental habitats. Helianthus anomalus was more fit than parental species in the H. anomalus actively moving desert dune habitat. The abilities to tolerate burial and excavation and to obtain nutrients appear to be important for success in the H. anomalus habitat. In contrast, H. deserticola failed to outperform the parental species in the H. deserticola stabilized desert dune habitat, and several possible explanations are discussed. The home site advantage of H. anomalus is consistent with environmental selection having been a mechanism for adaptive divergence and hybrid speciation and supports the use of H. anomalus as a valuable system for further assessment of environmental selection and adaptive traits.

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 score0.035
Threshold uncertainty score0.840

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.033
GPT teacher head0.283
Teacher spread0.249 · 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

Citations60
Published2010
Admission routes1
Has abstractyes

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