Bats provide an excellent case study for studying evolution due to their remarkable flight and echolocation capabilities. In this study, we sought to understand the phenotypic evolution of key traits in Rhinolophidae (horseshoe bats) using phylogenetic comparative methods. We aim to test the phylogenetic signals of traits and evaluated the best-fit evolutionary models given the data for each trait considering different traits may evolve under different models (i.e., Brownian Motion (BM), Ornstein-Uhlenbeck (OU) and Early Burst (EB)) and reconstruct ancestral character states. We examined how phenotypic characters are associated with echolocation calls and minimum detectable prey size. We measured 34 traits of 10 Asian rhinolophids species (187 individuals). We found that the majority of traits showed a high phylogenetic signal based on Blomberg’s K and Pagel’s λ, but each trait may evolve under different evolutionary models. Sella traits were shown to evolve under stabilizing selection based on OU models, indicating sella traits have the tendency to move forward along the branches toward some medial value in equilibrium. Our findings highlight the importance of sella characters in association with echolocation call emissions in Rhinolophidae, as calls are important for spatial cognition and also influence dietary preferences. Minimum detectable prey size in Rhinolophidae was associated with call frequency, bandwidth, call duration, wingspan and wing surface area. Ultimately, understanding trait evolution requires sensitivity due to the differential selective pressures which may apply to different characteristics.

Bats were captured using harp traps and released after measurements, photograph, tissue samples from biopsies punch and echolocation calls were recorded. The morphological measurements were made following Chornelia et al. (2022) which included external morphological measurements (forearm/FA, headbody/HB, hindfoot/HF, tibia/TB, ears/E, tail/Tail and mass/BM, noseleaf width/NLW, noseleaf height/NLL). External measurements were based on standard small mammal measurements following Francis (2019) using digital callipers Mitutoyo Absolute Series-500 (accuracy 0.01 mm) and body mass was measured with Pesola Spring Scale (Pesola® Präzisionswaagen AG, Switzerland) with a precision of 0.3%. For noseleaf measurements, we used photographic metrics following (Chornelia et al., 2022) including 14 characters (Internarial cup width/INCW, noseleaf area/NLA, sella area/SA, sella height/Sh, noseleaf length/NLL, noseleaf width/NLW, lancet-base width/LBW, lancet height/LH, lancet tip-height/LTH, lancet angle/Lang, lancet tip-connecting process/Ltcp, ratio of LTH/LH, ratio of LBW/LH, and sella base width/SBW). From wing photographs (taken on gridded paper) a total of 11 wing parameters were included in the analyses including wingspan/B, wing tip ratio/I, wing aspect ratio/AR, wing loading/WL, arm-wing length/Law, hand-wing length/ Lhw, arm-wing total surfaces area/Saw, hand-wing total surface area/Shw, ratio of Lhw and Law/TL, ratio of Shw and Saw/TS and total surface area of wing/S. Echolocation calls was collected from captured individual in the field and were recorded from hand-released. Calls were recorded using a Pettersson M500-384 (Pettersson Electronic AB, Uppsala, Sweden (www.batsound.com) and calls sequences were analysed using BatSound ver4 (Pettersson Electronic AB, Uppsala, Sweden) at sampling rate of 44.1 kHz and spectrogram was set at 1,024 sampling sites in Fast Fourier Transform (FFT) in conjunction with Hanning window. 

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