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Field estimates of reproductive success in a model insect: behavioural surrogates are poor predictors of fitness

2011· letter· en· W1597727248 on OpenAlexaff
D. J. Thompson, Christopher Hassall, Chris Lowe, Phillip C. Watts

Bibliographic record

VenueEcology Letters · 2011
Typeletter
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsCarleton University
FundersNatural Environment Research Council
KeywordsBiologyMatingOdonataEcologyReproductive successOffspringPopulationMating systemGenetic FitnessSeasonal breederZoologyDemographyBiological evolutionGenetics

Abstract

fetched live from OpenAlex

Understanding, and therefore measuring, factors that determine fitness is a central problem in evolutionary biology. We studied a natural population of Coenagrion puella (Odonata: Zygoptera) over two entire breeding seasons, with over a thousand individuals uniquely marked and genotyped, and all mating events at the rendezvous site recorded. Using a parentage analysis, fitness of individuals in the first generation was quantified as the numbers of offspring that survived to maturity. Although mating behaviour can be predicted by environmental and demographical variables, the numbers of mature offspring produced (fitness) cannot, and crucially, are poorly correlated with behavioural observations of mating. While fitness of both sexes was positively related to mating behaviour and to female's ectoparasite burden, these behavioural observations explained little more variance in offspring production than environmental and demographical variables. Thus, we demonstrate that behavioural measures of reproductive success are not necessarily reliable estimates of fitness in natural populations.

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 score0.118
Threshold uncertainty score0.611

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.055
GPT teacher head0.214
Teacher spread0.159 · 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
Published2011
Admission routes1
Has abstractyes

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