Patterns and causes of geographic variation in bat echolocation pulses

Abstract

Evolutionary biologists have a long-standing interest in how acoustic signals in animals vary geographically, because divergent ecology and sensory perception play an important role in speciation. Geographic comparisons are valuable in determining the factors that influence divergence of acoustic signals. Bats are social mammals and they depend mainly on echolocation pulses to locate prey, to navigate and to communicate. Mounting evidence shows that geographic variation of bat echolocation pulses is common, with a mean 5-10 kHz differences in peak frequency, and a high level of individual variation may be nested in this geographical variation. However, understanding the geographic variation of echolocation pulses in bats is very difficult, because of differences in sample and statistical analysis techniques as well as the variety of factors shaping the vocal geographic evolution. Geographic differences in echolocation pulses of bats generally lack latitudinal, longitudinal and elevational patterns, and little is known about vocal dialects. Evidence is accumulating to support the fact that geographic variation in echolocation pulses of bats may be caused by genetic drift, cultural drift, ecological selection, sexual selection and social selection. Future studies could relate geographic differences in echolocation pulses to social adaptation, vocal learning strategies and patterns of dispersal. In addition, new statistical techniques and acoustic playback experiments may help to illustrate the causes and consequences of the geographic evolution of echolocation pulse in bats.

Environmental correlates of geographic divergence in a phenotypic trait: A case study using bat echolocation

“…However, our results for R. damarensis indicate that temperature (AMT) was the predominant climatic factor responsible for the divergence in echolocation RF. This was also the case for R. ferrumequinum (Jiang et al., 2015) in Asia and for R. capensis in southern Africa. Similar to R. damarensis , R. capensis has a distribution that extends into the more arid western and northwestern regions of South Africa (Neumann & Bamford, 2015; Odendaal et al., 2014) and its RF was also not correlated with RH (Odendaal et al., 2014).…”

“…Most studies on geographic variation have focused on humidity as the main predictor of such variation (for a review see Jiang, Wu, & Feng, 2015) providing evidence that echolocating bats that are found in humid areas will experience severe atmospheric attenuation resulting in lower RF than those that are found in dry areas (Guillén et al., 2000; Heller & Von Helversen, 1989; Lawrence & Simmons, 1982). For example, geographic variation in the RF of R. pusillus was positively correlated with mean annual rainfall (Jiang et al., 2010).…”

“…For example, geographic variation in RF was positively correlated with mean annual rainfall in R. pusillus (Jiang et al., 2010) but negatively correlated with mean annual rainfall in Hipposideros ruber (Guillén et al., 2000). These contrary findings are often attributed to the complexity of natural selection (e.g., Jiang et al., 2015) but may also be a consequence of the nonlinear effects and potential collinearity of temperature and humidity on atmospheric attenuation (Luo et al., 2014). Neither Jiang et al.…”

“…Resting frequency variation may be the result of call frequency being passed from mother to infant through learning. In combination with female philopatry such learning could result in RF diverging among populations randomly by a process of cultural drift (see Jiang et al., 2015 for a review). However, the absence of any IbD signal and the association of RF variation with temperature and region suggest that other evolutionary processes rather than drift are responsible.…”

The effects of cultural drift on geographic variation in echolocation calls of the Chinese rufous horseshoe bat (Rhinolophus sinicus)

“…We corrected critical α values for multiple Mantel and partial Mantel tests by using Bonferroni adjustment (Rom, ). Considering the magnitude of effect that spatial scale has on geographic variation of acoustic signals (Jiang et al., ; Veselka, McGuire, Dzal, Hooton, & Fenton, ), we analyzed the geographic variation of RF at different spatial scales (Table ). Due to the insufficient significant difference between RF and climatic factors by using Mantel tests, a simple linear regression model was used to analyze their relationships.…”