Avian predators avoid attacking fly-mimicking beetles: A field experiment on evasive mimicry using artificial prey - Dataset & R Scripts

<br>Avian predators avoid attacking fly-mimicking beetles: A field experiment on evasive mimicry using artificial prey<br>Tadeu J. Guerra; e-mail: [e-mail] F. Braga; e-mail: [e-mail]ávio Camarota; e-mail: [e-mail] S. Neves; e-mail: [e-mail] W. Fernandes; e-mail: [e-mail]<br>This study describes the results of two field experiments using artificial beetle replicas made with nontoxic plasticine placed on host plants of a specialized fly-mimicking beetle species. The experiment_#1 evaluated three specific predictions. First, attack marks corresponding to beaks should be frequently observed in the beetle replicas. Second, we predicted that replicas with intermediate size (0,5 – 1,0 cm) should be more attacked by birds than those in the extreme size classes (0,25 – 2,0 and 4,0 cm). Third, we predicted that avian attacks on replicas should be higher in the peak of the wet season than during the peak of the dry season. The experiment_#2 manipulated the coloration pattern of beetle replicas to test the prediction that replicas with red patches would suffer less attacks by avian predators than control replicas not resembling red-eyed flies.The spreadsheet Experiment_#1_raw contains eight columns and 601 lines, where each line represents a single plasticine replica. The first column (#), designates plasticine replica number within each sample unity. The second column (Site) designates the area where blocks were stablished. The third column (Block) designates different locations where sample unities (groups of 10 plasticine replicas of each treatment) were subject to same spatial conditions. The fourth column (PlantTag) designates individual threes where replicas were placed. The fifth column (Season) designates period when the experiment was conducted. The sixth column (Size) designates size class of plasticine replicas. The seventh column (Attack) designates the occurrence of attack to replicas, and classification according to vestiges left on plasticine (bird - V or U-shaped beak marks; insects - small mouthparts perforations; mammal - teeth marks; missing - plasticine removed).The spreadsheet Experiment_#1 contains seven columns and 121 lines, where each line represents a sample unity, group of ten plasticine replicas of the same size within a block in each period. The first column (Site) designates the area where blocks were stablished. The second column (Block) designates different locations of groups of 10 plasticine replicas of each treatment. The third column (Season) designates period when the experiment was conducted. The fourth column (Size) designates size class of plasticine replicas. The fifth column (Total) designates the valid number of replicas in each sample unity. The sixth column (Attacked) designates the number of replicas with evidence of bird attack.The spreadsheet Experiment_#2_raw contains seven columns and 361 lines, where each line represents a single plasticine replica. The first column (#), designates plasticine replica number within each sample unity. The second column (Site) designates the area where blocks were stablished. The third column (Block) designates different locations where sample unities (groups of 10 plasticine replicas of each treatment) were subject to same spatial conditions. The fourth column (PlantTag) designates individual mistletoes where replicas were placed. The fifth column (Treatment) designates coloration pattern of plasticine replicas, classified in control, bad and good. The sixth column (Attack) designates the occurrence of attack to replicas, and classification according to vestiges left on plasticine (bird - V or U-shaped beak marks; insects - small mouthparts perforations; mammal - teeth marks; missing - plasticine removed).The spreadsheet Experiment_#2 contains five columns and 37 lines, where each line represents a sample unity, group of ten plasticine replicas of the same color pattern (Treatment) within a block. The first column (Site) designates the area where blocks were stablished. The second column (Block) designates different locations of groups of 10 plasticine replicas of each treatment. The third column (Treatment) designates color pattern of plasticine replicas. The fourth column (Total) designates the valid number of replicas in each sample unity. The fifth column (Attacked) designates the number of replicas with evidence of bird attack.The last spreadsheet (Coordinates) contains blocks’ geographical coordinates and elevation data.We analyzed data using R software (R Core Team, 2019). We employed generalized linear mixed effects models (GLMMs, glmer for non-normal datasets, with lme4 package in R) with fixed and random effects to analyze the datasets of replica attacks for experiments #1 and #2.In the experiment_#1 the explanatory variables Size (replica size classes, five levels: 0,25 – 0,5 – 1,0 – 2,0 – 4,0 cm) and Season (two levels: dry and wet) and the interaction among these factors were considered as fixed factors, whereas Site and Block were assigned as random effects accounting for spatial heterogeneity of samples. The response variable were the proportions of replicas exclusively attacked by avian predators after 14 days of exposure, calculated by dividing the variable Attacked by the variable Total. For this analysis we used data of the spreadsheet Experiment_#1.In the experiment_#2, the explanatory variable Treatment encompassed replica coloration with three levels (control – nor paint, bad – brown eyed, and good – red eyed) and was considered as a fixed factor and Site and Block assigned as random effect. The response variable were the proportions of replicas exclusively attacked by avian predators after 14 days of exposure, calculated by dividing the variable Attacked by the variable Total. For this analysis we used data of the spreadsheet Experiment_#2.The dataset of both experiments fitted binomial distribution error of the response variable. We selected the minimal models after the removal of non-significant variables (P-value &gt; 0.05). If we detected significant differences in variables with more than two levels (Size or Treatment), we performed contrast analysis to determine differences among levels. In both minimal models we checked for error distribution and data overdispersion.