Fig 1.
A summary of the predicted effects of lighting condition, habitat 3D variation and the interaction between direct lighting and 3D variation on the appearance of all animal patterns.
Upwards arrows indicate a positive effect on the phenotypic feature, e.g., increased luminance or directionality, while downwards arrows indicate a negative effect; a horizontal line indicates no predicted effect. Larger arrows indicate that increased variation increases the effect size of direct lighting, while smaller arrows indicate a reduction in effect size. For each prediction, the justification and relevant references are provided. CIE L*, a* and b* refer to the mean values of the opponent colour channels used by the CIELAB perceptual colour space [50]. These channels are L* (luminance, low = dark, high = light), a* (red-green, low = green, high = red) and b* (blue-yellow, low = blue, high = yellow).
Fig 2.
Schematic for experimental design using a meadow habitat as a demo.
(A) Prey pattern generation using CamoEvo patterns, spherical deformation and rendering. (B) Calibrated raw, gloss and rendered targets under diffuse (left) and direct (right) lighting conditions. (C) Virtual online predation experiment using 28 different habitats and 3 lighting conditions. Each treatment evolved for 20 generations with 24 targets per population. The selection of targets was based on a hybrid of the time taken to click on and the time taken to respond to the target (survival time). The target pattern used was a sample pattern shown from the last generation (gen = 20) of the direct lighting-only evolved condition for the chalk wildflower meadow habitat.
Fig 3.
A. Example change in phenotypic appearance for a population that improved in fitness (survival time). B.i) Average capture time increased over successive generations. Line colour is used to indicate the lighting treatments. These are direct (yellow), diffuse (blue), or mixed (grey, 50:50 direct and diffuse lighting). Dashed lines are used to indicate when the background is diffuse. 3D complexity is split into low (below the mean) and high (above the mean). B.ii) Each pane shows the log predictive value (slope) of different common camouflage metrics for the survival time of the camouflaged targets. These are luminance difference (absolute CIE L*difference), colour difference (Euclidean CIE a* and b* difference), pattern difference (sum CIE L* contrast difference across scales) and edge disruption (gabrat L*). Lower values for the difference metrics (luminance, colour, and pattern) indicate a greater match to the background. As a result, they should have a negative slope for fitness. For gabrat, higher values indicate greater edge disruption and so should instead have a positive correlation with fitness.
Fig 4.
Change in colour space and colour patterns.
A.i) Populations become increasingly similar to the mean colours of their local backgrounds (2.5x target radius) starting from a dispersed colour space. B.i) Example evolved targets from populations in low and high 3D variation habitats selected for under the different lighting treatments. B.ii) Hybrid violin & boxplots of PC1 for target patterns, where PC1 is predominantly large-scale luminance and colour contrast, and large horizontal (- vertical) patterns. Habitat 3D variation is split by the quantiles for the habitats’ mean depth variation across spatial scales.
Table 1.
Linear mixed model output effects of dominant substrate on the relationship between countershading gradient of the target-skin (CS) and substrate type on target survival time. Positive estimates and t values are shown in blue while negative values are shown in red. Model formula: Lmm (log(Survival Time) ~ CS_Gradient:dominantsubstrate+(1|Treatment)+(1|Habitat)).
Fig 5.
Phenotypic change in countershading and pattern shape.
A.i) Targets under direct and mixed lighting became increasingly positive in their luminance gradient. A.ii) Having a more positive render target gradient increased survival time for all substrates under both mixed and direct lighting, except for gravel under the direct lighting condition. B.i) Targets evolved under direct and mixed lighting conditions evolve a greater pattern contrast at larger spatial scales and across all scales when background 3D complexity is high. The red dotted line shows the targets in generation zero, dashed lines show the pattern energy of the diffuse and direct backgrounds. B.ii) Under direct lighting contrasting patterns are more directional and orient vertically against 3D complex backgrounds, arrows indicate whether the population average orientation is vertical or horizontal. Habitat 3D variation is split by the quantiles for the habitats’ mean depth variation across spatial scales.
Table 2.
Linear mixed model output effects of lighting treatment and 3D complexity on the unrendered target-skin’s contrast across spatial scales. Positive estimates and t values are shown in blue while negative values are shown in red. Model formula: lmm (patternenergy ~ Scale*Light*3D+(1|Treatment)+(1|Habitat) +(1|uniquephoto)).
Table 3.
Linear mixed model output effects of lighting treatment and background geometry on the evolved glossiness of the targets, relative to the maximum glossiness value they could have. Model formula: lmm (relativeglossiness ~ N-Gen * Light * 3Dvariation + (1|Treatment) + (1|Habitat)).