DOI: 10.5061/dryad.3n5tb2rrz
title: Túngara frog call-timing decisions arise as internal rhythms interact with fluctuating chorus noise

description: For chorusing males, optimally timing their calls relative to nearby
 rivals’ calls and fluctuations in background chorus noise is crucial for
 reproductive success. A caller’s acoustic environment will vary by chorus
 density and the properties of his chorus-mates’ calls and will fluctuate
 unpredictably due to chorusing dynamics emerging among his chorus-mates.
 Thus, callers must continuously monitor moment-to-moment fluctuations in
 the acoustic scene they perceive at the chorus for advantageous times to
 call. In live experimental choruses, we investigated the factors
 influencing túngara frog call-timing responses to chorus-mates’ calls on
 an interaction-by-interaction basis, revealing that intrinsic and
 extrinsic factors influenced call-timing decisions. Callers were more
 likely to overlap calls from smaller chorus-mates and chorus-mates at
 intermediate distances, as well as calls containing lower frequencies and
 exhibiting lower final amplitude minima. Consequently, variation among
 males in call properties led to variation in levels of call-interference
 received when calling in the same social environment. Additionally,
 callers were more likely to overlap chorus-mates’ calls after experiencing
 extended periods of inhibition and were less likely to overlap
 synchronized chorus-mates’ calls relative to single calls. In chorusing
 species, female choice is influenced by inter-caller dynamics, selecting
 for male call-timing strategies which, in turn, constitute the selective
 environment further refining these same strategies. Thus, understanding
 the specific factors driving call-timing decisions is essential for
 understanding how sexual selection operates in chorusing taxa.
description: In this study, we investigated call-timing interactions among
 male túngara frogs by recording calling patterns of interacting males
 within 6 experimental choruses of 6 callers each. We analysed underlying
 chorusing dynamics and investigated how inter-male variation in call
 properties influenced how chorus-mates related to one another’s
 calls.
description: # Túngara frog call-timing decisions arise as internal rhythms interact
 with fluctuating chorus noise Corresponding author:
 [luke.larter@utexas.edu](mailto:luke.larter@utexas.edu) ### Folder
 ‘Transition Probability Repeatability Analysis’ Contains R markdown file
 and CSV files to run analysis looking at how repeatable inter-caller
 transition patterns were over time (corresponding to analysis detailed in
 the first paragraph of the section titled ‘How Stable are Chorusing
 Dynamics Over Time?’ in the manuscript). *
 ‘*210927_001_SHORT_6_males_from_660_to_870_secs_transition_prob_matrix_first70.csv’*: a CSV containing a matrix of pair-wise inter-caller transition probabilities among all chorus-mates in chorus ID ‘210927_001’, for the first 70s of the entire 3.5-minute recording. ‘…*_second7*0.csv’ and ‘…*_third70.csv’* correspond to the second and third of the successive 70s, respectively. There are similar CSV files for each different chorus ID. * ‘*inter-caller_transition_probability_repeatability_analysis.rmd*’: Code using the above CSV files to analyse the repeatability of transition probabilities over time. More details are in the code comments. ### Folder ‘Overlap-Received Repeatability and SMA Regression’ Contains R markdown file and CSV files to run analysis looking at how repeatable individual variation in the degree of call overlap received from chorus-mates was over time (corresponding to analysis detailed in the second paragraph of section titled ‘How Stable are Chorusing Dynamics Over Time?’ in the manuscript). * ‘*210927_001_SHORT_6_males_from_660_to_870_secs_simple_overlap_proportion.csv*’: a CSV containing a data frame with the proportion of each chorus-mate calls that were overlapped by the call of at least one other chorus-mate for each of the successive 70s segments making up the overall 3.5-minute segment in chorus ID ‘210927_001’. Similar CSV files are present for all chorus IDs. ‘segment’ column is which 70s the value corresponds to (s1 = first 70s, s2 = second, s3 = third); ‘chorus_ID’ is chorus identifier; ‘caller_ID’ is the track ID of the chorus-mate; ‘num_calls’ is the number of calls that male produced in that segment, ‘num_overlapped’ is the number of these that were overlapped by at least one of his chorus-mates, ‘not_overlapped’ is the number that was not overlapped at all, and ‘overlap_props’ is the proportion of his calls that received overlap from at least one of his chorus-mates during that segment. * ‘*overlap_received_repeatablitity_analysis.rmd*’: Code using the above CSV files to analyse the repeatability of overlap received over time. More details in code comments ### Folder ‘Single Caller Transition Analysis GLMM’ Contains R markdown file and CSV files to run analysis looking at how variation in call properties influences how males related to the calls of chorus-mates (corresponding to analysis detailed in the section titled ‘Which Properties of Preceding Calls Influence the Probability of Call Overlap?’ in the manuscript). * ‘*single_caller_transition_data.csv*’: Dataframe with rows representing each following call made by all males in all choruses in this study, displaying whether they overlapped the call preceding them or not, and detailing the acoustic properties of that preceding call and the time that has elapsed since the following caller’s last call. ‘ID_focal_following_caller’ is the track ID of the following caller; ‘chorus_ID’ is chorus_identifier; ‘did_focal_follower_overlap_preceding_call_YN’ is the binary response denoting whether the following caller overlapped the preceding caller or not (1 = yes, 0 = no)’; ‘IOI_duration_preceding_focal_call’ is the time that has elapsed (inter-onset interval) since the last call by the following caller; ‘focal_svl’ is the snout-vent-length (body length) of the focal following caller (mm); ‘focal_mass’ is mass of the focal following caller (g); ‘focal_toe_clip_number’ is the permanent ID of the focal following caller (one male appeared in two different choruses, thus had two different ‘ID_focal_following_caller’ track IDs); ‘preceding_caller_svl’ is snout-vent length of preceding caller (mm); ‘preceding_caller_mass’ is mass of preceding caller (g); ‘preceding_caller_focal_toe_clip_number’ is the permanent ID of the preceding caller; ‘max_freq’ is the maximum frequency of the whine of the preceding caller (Hz); ‘min_freq’ is the minimum frequency of the whine of the preceding caller (Hz); ‘after_knee_amplitude_skewness’ is the amplitude skewness of the whine of the preceding caller; ‘min_last_150’ is the minimum final amplitude of the whine of the preceding caller relative to the maximum whine amplitude; ‘distance’ is the inter-caller distance between preceding and following callers (m). * ‘*single_caller_transition_analysis.rmd*’: Code using the above CSV to analyse the factors influencing overlap probability during inter-caller transitions from single preceding callers. More details are in the code comments. ### Folder ‘Synchronous Caller Transition Analysis GLMM’ * ‘*synchronous_caller_transition_data.csv*’: Data with rows representing each following call made by all males in all choruses in these studies, displaying whether they overlapped the call preceding them or not, and detailing the number of synchronous callers contributing to that preceding call and the time that has elapsed since the following caller’s last call. ‘ID_focal_following_caller’ is the track ID of the following caller; ‘chorus_ID’ is chorus_identifier; ‘did_focal_follower_overlap_preceding_call_YN’ is the binary response denoting whether the following caller overlapped the preceding caller or not (1 = yes, 0 = no)’; ‘IDs_synchronous_callers_preceding_focal_call’ is the list of the track IDs of the synchronous callers contributing to the preceding call (necessary for the multiple membership term in the GLMM); ‘Number_synchronous_callers_preceding_focal_call’ is the number of synchronous callers contributing to the preceding call; ‘IOI_duration_preceding_focal_call’ is the time that has elapsed (inter-onset interval) since the last call by the following caller; ‘focal_toe_clip_number’ is the permanent ID of the focal following caller (one male appeared in two different choruses, thus had two different ‘ID_focal_following_caller’ track IDs). * ‘*synchronous_caller_transition_analysis.rmd*’: ‘*single_caller_transition_analysis.rmd*’: Code using the above CSV to analyse the factors influencing overlap probability during inter-caller transitions from single or synchronous preceding callers. More details are in the code comments. ## Data/Code ### Version Information and Packages Used * RStudio v2021.09.0/351 running R v4.2.2 * tidyverse_v2.0.0 * lme4_v1.1.31 * DHARMa_v0.4.6 * rptr_v0.9.22 * smatr_v3.4.8 * MuMIn_v1.47.5 * sjPlot_v2.8.12 * ggplot2_v3.4.1 * lmerTest_v3.1.3 * car_v3.1.2 * splines_v4.2.2 * lmerMultiMember_v0.11.4 * ggridges_v0.5.4 * sna_v2.7.1 * lsa_v0.73.3 * afex v1.3-0