Nearly all research on camouflage has investigated its effectiveness for concealing stationary objects. However, animals have to move, and patterns that only work when the subject is static will heavily constrain behaviour. We investigated the effects of different camouflages on the three stages of predation-detection, identification and capture-in a computer-based task with humans. An initial experiment tested seven camouflage strategies on static stimuli. In line with previous literature, background-matching and disruptive patterns were found to be most successful. Experiment 2 showed that if stimuli move, an isolated moving object on a stationary background cannot avoid detection or capture regardless of the type of camouflage. Experiment 3 used an identification task and showed that while camouflage is unable to slow detection or capture, camouflaged targets are harder to identify than uncamouflaged targets when similar background objects are present. The specific details of the camouflage patterns have little impact on this effect. If one has to move, camouflage cannot impede detection; but if one is surrounded by similar targets (e.g. other animals in a herd, or moving background distractors), then camouflage can slow identification. Despite previous assumptions, motion does not entirely 'break' camouflage.

Iridescence as Camouflage Highlights d Iridescence in prey can serve a counterintuitive function: concealment d The effects of this protective function are further enhanced by glossy backgrounds d Iridescence, even for signaling purposes, may be less costly than previously thought d This newly discovered function may explain the widespread occurrence of iridescence

Iridescence is a taxonomically widespread and striking form of animal coloration, yet despite advances in understanding its mechanism, its function and adaptive value are poorly understood. We test a counterintuitive hypothesis about the function of iridescence: that it can act as camouflage through interference with object recognition. Using an established insect visual model (Bombus terrestris), we demonstrate that both diffraction grating and multilayer iridescence impair shape recognition (although not the more subtle form of diffraction grating seen in some flowers), supporting the idea that both strategies can be effective means of camouflage. We conclude that iridescence produces visual signals that can confuse potential predators, and this might explain the high frequency of iridescence in many animal taxa.

Static high contrast (‘dazzle’) patterns, such as zigzags, have been shown to reduce the perceived speed of an object. It has not escaped our notice that this effect has possible military applications and here we report a series of experiments on humans, designed to establish whether dynamic dazzle patterns can cause distortions of perceived speed sufficient to provide effective defence in the field, and the extent to which these effects are robust to a battery of manipulations. Dynamic stripe patterns moving in the same direction as the target are found to increase the perceived speed of that target, whilst dynamic stripes moving in the opposite direction to the target reduce the perceived speed. We establish the optimum position for such dazzle patches; confirm that reduced contrast and the addition of colour do not affect the performance of the dynamic dazzle, and finally, using the CO2 challenge, show that the effect is robust to stressful conditions.

Lay SummaryWe show that for objects moving in groups, spotting one that is a different shape is harder when the objects are similarly patterned. The difficulty of spotting the odd-one-out is further enhanced by matching the background and being in larger groups. So, even though motion ‘breaks’ camouflage, being camouflaged can help group-living animals reduce the risk of being singled out for attack by predators.

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Publicly available genetic summary data have high utility in research and the clinic including prioritizing putative causal variants, polygenic scoring, and leveraging common controls. However, summarizing individual-level data can mask population structure resulting in confounding, reduced power, and incorrect prioritization of putative causal variants. This limits the utility of publicly available data, especially for understudied or admixed populations where additional research and resources are most needed. While several methods exist to estimate ancestry in individual-level data, methods to estimate ancestry proportions in summary data are lacking. Here, we present Summix, a method to efficiently deconvolute ancestry and provide ancestry-adjusted allele frequencies from summary data. Using continental reference ancestry, African (AFR), Non-Finnish European (EUR), East Asian (EAS), Indigenous American (IAM), South Asian (SAS), we obtain accurate and precise estimates (within 0.1%) for all simulation scenarios. We apply Summix to gnomAD v2.1 exome and genome groups and subgroups finding heterogeneous continental ancestry for several groups including African/African American (~84% AFR, ~14% EUR) and American/Latinx (~4% AFR, ~5% EAS, ~43% EUR, ~46% IAM). Compared to the unadjusted gnomAD AFs, Summix's ancestry-adjusted AFs more closely match respective African and Latinx reference samples. Even on modern, dense panels of summary statistics, Summix yields results in seconds allowing for estimation of confidence intervals via block bootstrap. Given an accompanying R package, Summix increases the utility and equity of public genetic resources, empowering novel research opportunities.