Opposing effects of mortality factors on progeny operational sex ratio may thwart adaptive manipulation of primary sex ratio
Bibliographic record
Abstract
Abstract Despite extensive research on mechanisms generating biases in sex ratios, the capacity of natural enemies to shift or further skew operational sex ratios following sex allocation and parental care remains largely unstudied in natural populations. Male cocoons of the sawfly Neodiprion abietis (Hymenoptera: Diprionidae) are consistently smaller than those of females, with very little overlap, and thus, we were able to use cocoon size to sex cocoons. We studied three consecutive cohorts of N. abietis in six forest stands to detect cocoon volume‐associated biases in the attack of predators, pathogens, and parasitoids and examine how the combined effect of natural enemies shapes the realized operational sex ratio. Neodiprion abietis mortality during the cocoon stage was sex‐biased, being 1.6 times greater for males than females. Greater net mortality in males occurred because male‐biased mortality caused by a pteromalid parasitic wasp and a baculovirus was greater and more skewed than female‐biased mortality caused by ichneumonid parasitic wasps. Variation in the susceptibility of each sex to each family of parasitoids was associated with differences in size and life histories of male and female hosts. A simulation based on the data indicated that shifts in the nature of differential mortality have different effects on the sex ratio and fitness of survivors. Because previous work has indicated that reduced host plant foliage quality induces female‐biased mortality in this species, bottom‐up and top‐down factors acting on populations can affect operational sex ratios in similar or opposite ways. Shifts in ecological conditions therefore have the potential to alter progeny fitness and produce extreme sex ratio skews, even in the absence of unbalanced sex allocation. This would limit the capacity of females to anticipate the operational sex ratio and reliably predict the reproductive success of each gender at sex allocation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".