Effects of developmental plasticity and antagonistic selection on phenotypic variation in spiders
Bibliographic record
Abstract
In this dissertation, I ask whether developmental plasticity can explain the variation of phenotypic distributions as an adaptive response to variation in population demography and changes in the strength and direction of selection. I use three spider species to examine this question. Using a combination of field attraction and mark-recapture experiments, I first ask how male spiders locate females and the choices they make while mate searching. I demonstrate that males can distinguish between females of different species, populations and ages using long-distance pheromones, and that males increase mate searching risks because they are searching for specific females. As these long-distance pheromones can provide cues of female density, I next examine whether juvenile males alter their development when reared in the presence or absence of female's pheromones (cues of high and low female density, respectively). My results demonstrate that males alter their ontogeny to mature the phenotype that is most beneficial in the competitive context they are likely to experience at maturity. Males develop significantly faster when females are present, and are significantly larger and in better condition when females are absent. Since small size is apparently the result of a decision that is independent of resource availability, I next examine whether male fitness is phenotype specific. By testing small and large males in the competitive environments in which they mature, I show that although larger males are superior in direct competitions, smaller males have higher fitness when tested in the context that leads to their more rapid development. These results challenge the concept of male quality as a fixed trait value, demonstrating the necessity of taking life-history traits into consideration. I next use field populations to demonstrate that demographic variables fluctuate within a season, and depend on the scale of the examination. The strength of selection pressures also varied significantly throughout the breeding season. As a result, males are likely to experience different competitive challenges and selection pressures at different spatial and temporal scales, making a single phenotypic optimum unlikely. I end with a discussion regarding the adaptive nature of developmental plasticity, and when it is likely to evolve.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".