The Evolutionary Ecology of Flash Displays and Other Transiently Visible Anti-predation Signals
Bibliographic record
Abstract
Hidden signals is an umbrella term used to describe anti-predation signals that are not consistently visible but only exposed transiently. These signals have evolved independently numerous times in taxa ranging from insects to mammals. In spite of the fact that hidden signals are both conspicuous and abundant, we know relatively little about their evolution and function. The aims of this study are to answer two fundamental questions, 1. how do hidden signals generate a fitness benefit, and 2. what ecological circumstances precipitate their evolution? In order to address these questions, I have combined custom-built computer games and phylogenetic character analysis. The computer games use humans as model predators, and allowed us to simulate the deployment of hidden signals while manipulating specific parameters. The phylogenetic character analysis has allowed us to test whether certain morphological and behavioural traits are correlated with the evolution of hidden signals. By combining these two independent approaches we have been able to comprehensively evaluate a variety of hypotheses regarding the evolution of hidden signals. Chapter 1 summarizes the current knowledge of hidden signals. Chapter 2 describes an experimental "proof of concept", to determine if flash displays can generate a survival benefit through one specific proposed mechanism, namely a "decoy" effect. Chapter 3 describes a phylogenetic analysis used to test whether body size (a well-known predictor of predation risk), is correlated with the evolution of hidden signals across a range of insect taxa. Chapter 4 describes an experimental test of the efficacy of startle signals in deterring an insect predator. Chapter 5 combines an experimental and phylogenetic evaluation of the implications of flight initiation distance on the anti-predation benefit of flash displays. Finally, in Chapter 6 I summarize my thoughts on the collective implications of my thesis work. Overall, I argue that hidden signals are an ecologically important adaptation that can prevent attacks through multiple mechanisms and may be selected for by a variety of predator taxa.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".