DOI: 10.5061/dryad.q4b78
title: Data from: Optimal background matching camouflage

description: Background matching is the most familiar and widespread camouflage
 strategy: avoiding detection by having a similar colour and pattern to the
 background. Optimizing background matching is straightforward in a
 homogeneous environment, or when the habitat has very distinct sub-types
 and there is divergent selection leading to polymorphism. However, most
 backgrounds have continuous variation in colour and texture, so what is
 the best solution? Not all samples of the background are likely to be
 equally inconspicuous, and laboratory experiments on birds and humans
 support this view. Theory suggests that the most probable background
 sample (in the statistical sense), at the size of the prey, would, on
 average, be the most cryptic. We present an analysis, based on realistic
 assumptions about low-level vision, that estimates the distribution of
 background colours and visual textures, and predicts the best camouflage.
 We present data from a field experiment that tests and supports our
 predictions, using artificial moth-like targets under bird predation.
 Additionally, we present analogous data for humans, under tightly
 controlled viewing conditions, searching for targets on a computer screen.
 These data show that, in the absence of predator learning, the best single
 camouflage pattern for heterogeneous backgrounds is the most probable
 sample.
description: Day 3 003_srgb_1_to_day2
 083_srgb_5_humancontains the L*a*b* and
 Gabor filter outputs of all 505 samples of bark, as seen by Human visual
 systems. Filename+photo= Name of image. rep= number of sample from each
 image (5 for each image). L= L value of L*a*b*, a= a value of L*a*b*, b= b
 value of L*a*b*. fxoy= f: the gabor filter’s spatial frequency (1-4 from
 fine to coarse), o: the gabor filter’s orientation (1-6 from 0 to 150° in
 30° increments)Day 3 003_srgb_1_to_day2
 083_srgb_5_birdcontains the L*a*b* and
 Gabor filter outputs of all 505 samples of bark, as seen by Bird visual
 systems. Filename+photo= Name of image. rep= number of sample from each
 image (5 for each image). L= L value of L*a*b*, a= a value of L*a*b*, b= b
 value of L*a*b*. fxoy= f: the gabor filter’s spatial frequency (x=1-4 from
 fine to coarse), o: the gabor filter’s orientation (y=1-6 from 0 to 150°
 in 30° increments)Survival
 Experimentcontains all the data
 from the field experiment. Columns: Block= number of block, Treatment: A=
 treatment with common colours and textures, B: uncommon colours and
 textures, C: Uncommon colour but common texture, D: Common colour but
 uncommon texture. Replicate= the number of the sample in each treatment.
 Time: Hours of survival of each target. Censor= 1: Successful predation by
 bird, 0: censored data (not taken by bird). Notes= Cause of target’s
 removal.bark_RGBnTextures (human
 exp)Contains the RGB and
 Gabor filter outputs of the backgrounds used in the human experiment.
 Filename= Name of image file. photo=name of bark, rep= number of sample
 from each image (5 for each image). R= R value of RGB, G= G value of RGB,
 B= B value of RGB. fxoy= f: the gabor filter’s spatial frequency (1-4 from
 fine to coarse), o: the gabor filter’s orientation (1-6 from 0 to 150° in
 30° increments)target_RGBnTextures
 (human exp)Contains the RGB and
 Gabor filter outputs of the targets extracted from the backgrounds that
 were used in the human experiment. Filename= Name of image file.
 photo=name of target, rep= number of sample from each image (5 for each
 image). R= R value of RGB, G= G value of RGB, B= B value of RGB. fxoy= f:
 the gabor filter’s spatial frequency (1-4 from fine to coarse), o: the
 gabor filter’s orientation (1-6 from 0 to 150° in 30°
 increments)KostasExptAllContains all the results taken from each participant during the Human experiment. Filename: name of test image. infile: name of background from where the target was extracted. infile2= name background. blank=blank column. filenum= the number of the stimuli+background combination. mothsource= the number of the moth (1-48). barksource= the number of the bark (1-48). cutrow= the row of the image from which the target was taken. cutcol= the column of the image from which the target was taken. pasterow= the row of the background image on which the target was placed. pastcol= the column of the background image on which the target was placed.