Testing drivers of acoustic divergence in cicadas (Cicadidae: Tettigettalna)

Abstract

Divergence in acoustic signals may have a crucial role in the speciation process of animals that rely on sound for intra-specific recognition and mate attraction. The acoustic adaptation hypothesis (AAH) postulates that signals should diverge according to the physical properties of the signalling environment. To be efficient, signals should maximize transmission and decrease degradation. To test which drivers of divergence exert the most influence in a speciose group of insects, we used a phylogenetic approach to the evolution of acoustic signals in the cicada genus Tettigettalna, investigating the relationship between acoustic traits (and their mode of evolution) and body size, climate and micro-/macro-habitat usage. Different traits showed different evolutionary paths. While acoustic divergence was generally independent of phylogenetic history, some temporal variables' divergence was associated with genetic drift. We found support for ecological adaptation at the temporal but not the spectral level. Temporal patterns are correlated with micro- and macro-habitat usage and temperature stochasticity in ways that run against the AAH predictions, degrading signals more easily. These traits are likely to have evolved as an anti-predator strategy in conspicuous environments and low-density populations. Our results support a role of ecological selection, not excluding a likely role of sexual selection in the evolution of Tettigettalna calling songs, which should be further investigated in an integrative approach.

Keywords: acoustic signals; cicada; ecological selection; evolution; phylogenetic comparative analysis.

FIGURE 1

Sampling locations. (a) Sampling locations for 11 Tettigettalna species. (b) Sampling locations of T. argentata lineages.

FIGURE 2

Tettigettalna species tree from Costa (2017). Dots refer to habitat characterization. Red dots: Shrubby species; grey dots: Arboreal species; dark grey dots: High NDVI; light green dots: low NDVI.

FIGURE 3

Species habitat characterization. (a) Calling site: percentage of individuals found on arboreal (grey bars) and shrubby (red bars) calling sites in each specie. (b) NDVI: average NDVI value found for each species. NDVI binary classification based on a cut‐of off 0.42 (low < 0.42 high ≥ 0.42): Dark green bars—high NDVI; light green bars—low NDVI. Showpiece of the habitat of a (c) shrubby species in a high NDVI location (T. h. galantei Type II in Pinos Genil, Sierra Nevada, Spain); (d) shrubby species in a low NDVI location (T. h. helianthemi in Caniles, Granada, Spain) and (e) arboreal species in a high NDVI location (T. mariae in Cartaya, Huelva, Spain).

FIGURE 4

Correlated evolution between calling site and NDVI and acoustic variables. (a) NDVI and number of echemes (NE); (b) NDVI and echeme duration (ED); (c) calling site and interval duration (ID).

FIGURE 5

Phylomorphospace plot of temporal acoustic space. (a) PC1 vs. PC2 and (b) PC1 vs PC3. The first three principal components account for 93% of the total variation. Red dots: shrubby species; grey dots: arboreal species; dots with dark green trace: high NDVI; dots with light green trace: low NDVI. White dots: ancestral states.