Field estimates of reproductive success in a model insect: behavioural surrogates are poor predictors of fitness
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".