DOI: 10.5061/dryad.v41ns1s83
title: Data from: Camouflage using surface disruption: the importance of corners versus edges

description: Disruptive colouration is a common mode of camouflage used by predators
 and prey to conceal their body contours. Several studies have noted the
 importance of edge disruption in breaking up two-dimensional (2D) body
 outlines, but less is known about how disruptive colouration hinders the
 detection and recognition of three-dimensional (3D) body shapes.
 Specifically, in the context of animal camouflage, it is not clear how the
 location of three-dimensional (3D) surface disruption affects prey
 detection. In human visual systems, it is known that corners, not edges,
 of an object are critical for shape processing and contour completion.
 However, whether corners are also critical for 3D shape recognition in
 non-human animals has not been investigated. To test this, in Experiment
 1, we presented 3D-printed moth-like targets with either corner
 disruption, edge disruption, or no disruption to wild, free-living birds.
 We repeated this in Experiment 2 with 2D targets, comprising images
 matched to Experiment 1, to determine if pictorial cues (patterns that
 produce an impression of depth) had the same effect. Contrary to our
 predictions, we found no effect of surface disruption location on survival
 probability for either 3D or 2D moth targets. Contrary to previous work,
 we found that targets with disrupted surfaces, irrespective of the
 disruption location, did not have higher survival than those with
 continuous surfaces. However, when the data from both experiments were
 combined, we found that 3D targets had higher survival than 2D targets.
 Although the disruptive and non-disruptive targets differed in contrast,
 this did not account for the variation in survival. Indeed, most of the
 variation in our data was explained by the spatial and temporal structure
 of the data, owing to different predator communities and seasonal
 variation in predation risk. Given that corners are critical for shape
 recognition in humans, developing an appropriate system to test visual
 perception in non-human animals will provide key insights into the role of
 visual perception in the predator-prey arms race.
description: # Data from: Camouflage using 3D surface disruption: the importance of
 corners versus edges
 [https://doi.org/10.1002/ece3.72052](https://doi.org/10.1002/ece3.72052)
 ## Description of the data and file structure The attached data (.csv
 files) and code (R scripts) are for three separate analyses: 1. Analysis
 of 3D targets (Experiment 1) 2. Analysis of 2D targets (Experiment 2) 3.
 Analysis of both Experiments 1 & 2 combined ### Files and variables
 #### File: Supporting_R_code_3D_survival.R **Description:** R code for
 analysing the results of experiment 1 (3D targets). #### File:
 BOTHEXPS.csv **Description:** Survival data for Experiment 1 (3D targets)
 ##### Variables * Block: Replicate ID, each block was carried out in a
 separate part of the woodland * Treat: Target treatment code (6
 treatments) * Surv_time: Survival time in hours * Cens: Target censored (1
 = taken by bird predator) or not (0 = target present at last check or
 taken by non-bird predator) * Year: Whether the experiment was performed
 in November 2023 or April 2024 #### File: Supporting_R_code_2D_survival.R
 **Description:** R code for analysing the results of experiment 2 (2D
 targets). #### File: 2D_Image_data_no_outliers.csv **Description:** Image
 data for Experiment 2 (data from photographs of targets on trees) #####
 Variables * EXPERIMENT: Location of fieldwork in Noggerup (November 2023)
 or Wilga (April 2024), Western Australia. * BLOCK: Replicate ID, each
 block was carried out in a separate part of the woodland. Coded separately
 by location. * Block2: Replicate ID, each block was carried out in a
 separate part of the woodland. Coded continuously. * Label: Name of image
 used to collect data * photoCheck: Additional code of another image of the
 target (typically two photographs were taken). * Cens: Target censored (1
 = taken by bird predator) or not (0 = target present at last check or
 taken by non-bird predator) * Surv_Time: Survival time in hours *
 Treat: Target treatment code (6 treatments) * lumMean: Mean luminance of
 target (modelled for bird vision) * lumSD: Standard deviation of luminance
 (modelled for bird vision) * area: Measurement area in pixels * lwMean:
 Mean cone catch for long wavelength cones (modelled for bird vision) *
 lwSD: Standard deviation of cone catch for long wavelength cones (modelled
 for bird vision) * mwMean: Mean cone catch for medium wavelength cones
 (modelled for bird vision) * mwSD: Standard deviation of cone catch for
 medium wavelength cones (modelled for bird vision) * swMean: Mean cone
 catch for short wavelength cones (modelled for bird vision) * swSD:
 Standard deviation of cone catch for short wavelength cones (modelled for
 bird vision) * dblMean: Mean cone catch for double cones (modelled for
 bird vision) * dblSD: Standard deviation of cone catch for double cones
 (modelled for bird vision) #### File: Supporting_R_code_3D_2D_combined.R
 **Description:** R code for analysing the results of Experiments 1 & 2
 combined #### File: Ruby_jen_both_experiments.csv
 **Description:** Survival data for Experiments 1 and 2 combined #####
 Variables * year: Whether the experiment was performed in 2023 or 2024 *
 Experiment: Whether target type was 3D (Experiment 1) or 2D (Experiment 2)
 * Tree: Tree ID (each target was pinned on 60 trees per block) *
 Block: Replicate ID, each block was carried out in a separate part of the
 woodland * Treat: Target treatment code (6 treatments) * Cens: Target
 censored (1 = taken by bird predator) or not (0 = target present at last
 check or taken by non-bird predator) * Surv_time: Survival time in hours
 #### File: LumResultsPooledLASTCHECK_Outlier.csv **Description:** Image
 data for Experiment 1 (data from photographs of targets on trees) #####
 Variables * EXPERIMENT: Whether the experiment was performed in November
 or April * BLOCK: Replicate ID, each block was carried out in a separate
 part of the woodland * Label: Name of image used to collect data *
 Treatment: Target treatment code (6 treatments) * Surv_Time: Survival time
 in hours * Cens: Target censored (1 = taken by bird predator) or not (0 =
 target present at last check or taken by non-bird predator) * lumMean:
 Mean luminance of target (modelled for bird vision) * lumSD: Standard
 deviation of luminance (modelled for bird vision) * area: Measurement area
 in pixels * lwMean: Mean cone catch for long wavelength cones (modelled
 for bird vision) * lwSD: Standard deviation of cone catch for long
 wavelength cones (modelled for bird vision) * mwMean: Mean cone catch for
 medium wavelength cones (modelled for bird vision) * mwSD: Standard
 deviation of cone catch for medium wavelength cones (modelled for bird
 vision) * swMean: Mean cone catch for short wavelength cones (modelled for
 bird vision) * swSD: Standard deviation of cone catch for short wavelength
 cones (modelled for bird vision) * dblMean: Mean cone catch for double
 cones (modelled for bird vision) * dblSD: Standard deviation of cone catch
 for double cones (modelled for bird vision) #### File:
 Jen_survival_both_years_no_nas.csv **Description:** Survival data for
 Experiment 2 (2D targets) ##### Variables * year: Whether the experiment
 was performed in 2023 or 2024 * Tree: Tree ID (each target was pinned on
 60 trees per block) * Block: Replicate ID, each block was carried out in a
 separate part of the woodland * Treat: Target treatment code (6
 treatments) * Cens: Target censored (1 = taken by bird predator) or not (0
 = target present at last check or taken by non-bird predator) *
 Surv_time: Survival time in hours ## Code/software The scripts are for R
 and were run using RStudio software (version 4.4.2). The following R
 packages were used: coxme, dplyr, ggplot2, nlme, lme4, survival, survminer
 ## Access information No publicly accessible locations of the data or data
 sources. Please contact the authors for access to the images of targets.