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Interspecific seed discounting and the fertility cost of hybridization in an endangered species

2007· article· en· W2064844646 on OpenAlexaff
Kevin S. Burgess, Martin Morgan, Brian C. Husband

Bibliographic record

VenueNew Phytologist · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of GuelphUniversity of Toronto
Fundersnot available
KeywordsInterspecific competitionInterspecific hybridizationEndangered speciesBiologyDiscountingFertilityEcologyReproductive isolationBotanyEvolutionary biologyHybridEconomicsDemographyPopulationHabitat

Abstract

fetched live from OpenAlex

Hybrid fertilizations can have negative demographic effects on taxa by usurping ovules that would otherwise give rise to nonhybrid offspring. The consequent reduction in conspecific matings may be exaggerated in rare taxa and constitutes a fertility cost that has rarely been quantified. Here, the effect of interspecific mating was estimated on the fecundity of locally rare red mulberry (Morus rubra), which hybridizes with introduced white mulberry (Morus alba) and red yen white hybrids. First, the asymmetry in pollen production among red, white and hybrid mulberry in two sympatric populations was quantified. The fertility cost of hybridization was then assessed experimentally by estimating seed production and rates of interspecific mating in red mulberry trees from plots where white and hybrid mulberry trees were selectively removed. On average, the percentage of mulberry pollen per plot produced by red mulberry (8%) was significantly lower than the mean for white and hybrid mulberry combined (92%). Experimentally removing white and hybrid mulberry increased the siring fertility of red mulberry by 14% but produced no change in seed set. Results indicate that seeds of red mulberry, ordinarily sired by conspecific pollen, are being discounted through fertilization of ovules by heterospecific pollen, which may contribute to local decline of red mulberry.

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 score0.030
Threshold uncertainty score0.987

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 science0.0000.000
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 head0.021
GPT teacher head0.265
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.

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

Citations77
Published2007
Admission routes1
Has abstractyes

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