DOI: 10.5061/dryad.6djh9w1d3
title: Data from: Recognition of predator cues hinders social communication

description: Antipredator defenses often rely on perception and discrimination of cues
 from predators, and alteration of behavior by potential prey.
 Characteristics of acoustic signals allow eavesdropping on calls of
 predators, permitting listeners to gauge predation risk by assessing the
 location and identity of the signaler. We tested the ability of bats that
 are preyed upon by other bats to discriminate between echolocation calls
 of predators and non-predators, and the impact of risk reduction
 strategies on communication and sociality. Bats distinguished between
 echolocation calls of predators and non-predators, recognizing predator
 calls with high accuracy. However, bats were more cautious when the
 structure of non-predator calls was similar to predator calls. In the
 presence of predator calls, bats ceased social communication, impacting
 sociality and disrupting group cohesion.
description: # Recognition of predator cues hinders social communication Dataset DOI:
 [10.5061/dryad.6djh9w1d3](10.5061/dryad.6djh9w1d3) ## Description of the
 data and file structure **Title of project** Recognition of predator cues
 hinders social communication and group cohesion **Authors** Melquisedec
 Gamba-Rios, Gary F. McCracken and Gloriana Chaverri **General
 information** We tested the ability of bats that are preyed upon by other
 bats to discriminate between echolocation calls of predators and
 non-predators, and the impact of risk reduction strategies on
 communication and sociality. ### Files and variables #### File: data.csv
 **Description:** Data for number of response calls emitted per individual
 and treatment. ##### Variables * bat: unique identifier of individuals *
 experiment: type of echolocation calls emitted during the trial in the
 order in which they were presented to focal bats (C: control, P: predator,
 F: frugivorous, I: insectivorous) * order: the order in which non-predator
 (NP) or predator (P) calls were emitted, with NP-P being experiments in
 which the non-predator was presented first, and P-NP being experiments in
 which the predator was presented first. * treatment: identifies if the
 response calls quantified correspond to events in which a predator or
 non-predator echolocation call was broadcast * bat_type: identifies the
 type of echolocation calls (control, carnivorous, frugivorous,
 insectivorous) that were being emitted when responses were quantified *
 period: determines if data on number of responses were collected before,
 during, or after the emission of echolocation calls * response: number of
 response calls emitted by the focal bat #### File: calls.xlsx
 **Description:** Echolocation call parameters for the species used during
 playback. ##### Variables * duration: Duration of the call in seconds (s).
 * disttomax: Time from call start to point of maximum amplitude, in
 seconds (s). * spectral parameters: peak freq(...): Peak frequency at that
 time point, in Hertz (Hz); min freq(...): Minimum frequency at that time
 point, in Hz; max freq(...): Maximum frequency at that time point, in Hz;
 entropy(...): Spectral entropy (unitless), a measure of signal complexity;
 lower values = more tonal calls, higher values = more noisy or broadband
 calls. Each one of these parameters was measured at different temporal
 points within the call: (start), (end), (centre), (max), (mean), and (0)
 through (4). These temporal points represent: start: beginning of the
 call, end: end of the call, centre: midpoint of the call, max: time of
 maximum amplitude, mean: average across the entire call, 0 to 4: equally
 spaced time segments along the call duration. * bat_type: determines
 whether a given call belonged *Vampyrum spectrum* (carnivorous bat),
 *Uroderma convexum* (frugivorous bat), *Rhogeessa io* (sympatric
 insectivorous bat) or *Molossops temminckii* (non-sympatric insectivorous
 bat) **Code/Software** **Analyses.R**: This R script analyzes bat
 behavioral responses to acoustic stimuli using generalized linear mixed
 models, PCA, clustering, and signal detection theory. It also generates
 statistical plots and figures for publication. ## Access information Other
 publicly accessible locations of the data: *
 [https://github.com/morceglo/Predator-recognition.git](https://github.com/morceglo/Predator-recognition.git)