DOI: 10.5061/dryad.73n5tb35d
title: Data from: Evasive maneuvers adopted by mosquitoes reveal plasticity in the echolocation of Myotis riparius (Vespertilionidae)

description: Evasive maneuvers are essential behaviors to escape predator attacks.
 Several studies describe the advantages of evasive maneuvers when adopted
 by eared moths, under the risk of attack by bats. However, little is known
 about this behavior when expressed by dipterans in natural environments.
 This study describes, for the first time, two distinct behaviors adopted
 by mosquitoes in flight during attacks by insectivorous bats in riverine
 environments. Antipredatory behaviors differ greatly among themselves and,
 consequently, in their success in avoiding predation. In both cases, bats
 seek to adjust the parameters of their calls to maximize their chances of
 capturing mosquitoes. The results indicate that mosquitoes are capable of
 detecting the approach of bats and reacting appropriately, however success
 in escaping is associated with the type of maneuver and of the
 microhabitat where the interaction occurs.
description: To test the first hypothesis, was used a chi-square test to
 assess differences in the observed and expected number of successful bat
 attacks, considering the manifestation of each antipredator behaviors
 (different prey species) as the null hypothesis. To test the second
 hypothesis, I used Student's t test for paired samples was used to
 assess whether there were differences in the following acoustic
 parameters; (i) <em>Fmax</em> - maximum frequency (kHz), (ii)
 <em>Fmin</em> - minimum frequency (kHz), (iii) PF - peak
 frequency (kHz), (iv) Bandwidth (kHz), (v) duration of the pulses (ms) and
 (vi) interval between pulses (ms). These comparisons was being
 individually for the search, approach and feeding buzz phases emitted by
 bats during attacks. The paired t-test is the most appropriate analysis
 because the ultrasonic recordings recorded during the bats attack on each
 of the two mosquito species were collected at the same sites with
 standardized sampling effort, making the samples
 non-independent. The time parameters of the oscillogram
 were measured while the frequency parameters were obtained from the power
 spectrum (Ratcliffe & Jakobsen, 2018). Acoustic data were analyzed
 using Raven 1.5 software (Charif et al., 2008). Calls were processed with
 automatic element separation using -20 dB maximum amplitude. The pulses
 were plotted simultaneously on the spectrogram, showing the relationship
 between frequency, time and intensity. Spectrograms were constructed from
 Fast Fourier Transforms size at 512, contrast at 68 and brightness at 63.
 All spectral parameters are given as mean ± 1 SD. To
 test the first hypothesis, was used a chi-square test to assess
 differences in the observed and expected number of successful bat attacks,
 considering the manifestation of each antipredator behaviors (different
 prey species) as the null hypothesis. To test the second hypothesis, I
 used Student's t test for paired samples was used to assess whether
 there were differences in the following acoustic parameters; (i)
 <em>Fmax</em> - maximum frequency (kHz), (ii)
 <em>Fmin</em> - minimum frequency (kHz), (iii) PF - peak
 frequency (kHz), (iv) Bandwidth (kHz), (v) duration of the pulses (ms) and
 (vi) interval between pulses (ms). These comparisons was being
 individually for the search, approach and feeding buzz phases emitted by
 bats during attacks. The paired t-test is the most appropriate analysis
 because the ultrasonic recordings recorded during the bats attack on each
 of the two mosquito species were collected at the same sites with
 standardized sampling effort, making the samples
 non-independent. The time parameters of the oscillogram
 were measured while the frequency parameters were obtained from the power
 spectrum (Ratcliffe & Jakobsen, 2018). Acoustic data were analyzed
 using Raven 1.5 software (Charif et al., 2008). Calls were processed with
 automatic element separation using -20 dB maximum amplitude. The pulses
 were plotted simultaneously on the spectrogram, showing the relationship
 between frequency, time and intensity. Spectrograms were constructed from
 Fast Fourier Transforms size at 512, contrast at 68 and brightness at 63.
 All spectral parameters are given as mean ± 1 SD.
description: # Breviglieri C. P. B. 2024. Evasive maneuvers adopted by mosquitoes
 reveal plasticity in the echolocation of Myotis riparius
 (Vespertilionidae)
 [https://doi.org/10.5061/dryad.73n5tb35d](https://doi.org/10.5061/dryad.73n5tb35d) Data referring to the average values obtained for each of the attacks recorded by the recorder. ## Description of the data and file structure The files provided include three data tables, with the acoustic parameters obtained during the search phase (T_test_Search_calls), approach (t_Test_approach_phase) and terminal phase (T_test_Terminal_phase) and the script created (R script_manuscript ID ETH_24_0104). The file "T_test_Search_calls" refers to the acoustic parameters emitted by the bats during the search phase (foraging). The file "t_Test_approach_phase" refers to the acoustic parameters emitted by the bats during the approach phase, that is, when they detected the prey. The file "T_test_Terminal_phase" refers to the acoustic parameters emitted by the bats during the terminal phase or as it is also called "Buzz", that is, when the bat attacks the prey. For all cases, the abbreviation of the parameter names is: Mosquitoes: Species of mosquitoes studied (Genus) Fmax: Maximum frequency Fmin: Minimum frequency PF: Frequency peak Durat: Duration of calls Bandw. Bandwidth Pulses: Interval between calls Number: Number of pulses analyzed The file "R script_manuscript ID ETH_24_0104" presents all the codes used for the manuscript analyses (Script). \###################################################################### To run the analyses, follow the instructions below: First, load the packages: library(ggplot2) library(ggpubr) \############################################################### To open the data sheet, run the command: obj=read.table(file.choose(), header=TRUE) \############################################################################# choose the first sheet, referring to the call parameters search: T_test_Search_calls \########################################################## Check if the table was loaded correctly: obj Example of table: \&gt; obj mosquitoes Fmax Fmin PF Durat Bandw Pulse 1 culex 56.76 42.69 46.50 5.08 7.00 80.00 2 culex 58.03 43.72 46.50 5.08 6.50 79.80 3 culex 57.52 42.44 46.50 4.40 7.50 79.60 4 culex 57.52 43.20 46.00 5.08 6.00 80.00 5 culex 55.52 42.69 46.00 4.77 7.50 80.00 6 culex 57.53 43.30 46.30 5.10 7.50 79.90 7 aedes 56.73 43.63 46.56 5.09 7.00 80.02 8 aedes 57.55 43.66 46.48 5.12 6.50 79.80 9 aedes 58.01 43.55 46.55 4.62 7.43 79.60 10 aedes 57.52 43.30 46.39 5.03 6.80 80.00 11 aedes 55.52 43.22 46.50 4.97 7.50 80.00 12 aedes 57.51 43.41 46.44 5.04 7.50 79.90 \############################################### Remember that the abbreviations refer to the following acoustic parameters: Mosquitoes: Species of mosquitoes studied (Genus) Fmax: Maximum frequency Fmin: Minimum frequency PF: Frequency peak Durat: Duration of calls Bandw. Bandwidth Pulses: Interval between calls Number: Number of pulses analyzed \######################################################### Then, start the analysis for each of the acoustic parameters. ## Fmax = maximum frequency t.test(Fmax ~ mosquitoes, paired = TRUE, data = obj) Example of the first result: Result: Paired t-test data: Fmax by mosquitoes t = -0.053176, df = 5, p-value = 0.9597 alternative hypothesis: true mean difference is not equal to 0 95 percent confidence interval: -0.3289420 0.3156086 sample estimates: mean difference -0.006666667 In this case, there were no differences, so the boxplot was not developed. \###################################################### Now, here is an example of the analysis regarding the maximum frequency (kHz) emitted during the approach phase. Differences were detected in this and, therefore, the boxplot was created. To open the data sheet, run the command: obj=read.table(file.choose(), header=TRUE) \############################################################ choose the sheet, referring to the search call parameters: t_Test_approach_phase \############################################################ Check if the table was loaded correctly: obj Example of table: \&gt; obj mosquitoes Fmax Fmin PF Durat Bandw Pulse Number 1 culex 69.27 39.22 48.50 1.65 7.71 9.99 10 2 culex 69.21 38.71 48.50 1.70 7.75 10.02 9 3 culex 69.27 39.04 49.00 1.65 7.74 9.26 10 4 culex 68.93 38.72 48.82 1.63 7.71 9.38 9 5 culex 69.28 38.72 48.89 1.61 7.71 9.89 9 6 culex 69.27 38.23 48.90 1.63 7.75 10.05 10 7 aedes 75.80 39.22 51.50 1.51 5.91 16.05 4 8 aedes 75.21 40.21 51.50 1.82 6.00 15.26 4 9 aedes 76.17 39.24 51.00 1.51 5.93 16.00 4 10 aedes 74.71 39.72 50.82 1.50 6.11 16.04 4 11 aedes 75.28 40.19 51.89 1.51 6.09 16.05 4 12 aedes 75.17 40.23 50.90 1.50 5.94 15.05 4 \######################################################### Then, start the analysis for each of the acoustic parameters. &gt; t.test(Fmax ~ mosquitoes, paired = TRUE, data = obj) Example of the first result: Paired t-test date: Fmax by mosquitoes t = 34.868, df = 5, p-value = 3.651e-07 (difference detected) alternative hypothesis: true mean difference is not equal to 0 95 percent confidence interval: 5.729021 6.640979 sample estimates: mean difference 6,185 ###### ######################################################\# \# Boxplot Para criar o boxplot referente a este parametro seguir o comando abaixo: ggplot(data = obj, aes(x= mosquitoes, y= Fmax, color = mosquitoes)) + labs(x = "Species of mosquitoes", y = "Fmax - maximum frequency (kHz)") + scale_y_continuous(limits = c(67.0, 78.0)) + geom_boxplot(fill=c("coral", "coral"), color="black", ``` outlier.shape = NA, alpha = 0.5) + ``` geom_jitter(shape = 16, position = position_jitter(0.1), cex = 20, alpha = 1) + scale_color_manual(values = c("black", "black")) + theme_bw(base_size = 20) + theme(axis.text.y = element_text(size = 20)) + theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank()) + theme(legend.position = "none") \############################################################## Therefore, to redo the analyses and boxplots, follow the available script. Don't forget to open the correct spreadsheets for each of the echolocation phases (search phase -&gt; T_test_Search_calls, approach -&gt; t_Test_approach_phase and terminal phase -&gt;T_test_Terminal_phase)