Phenotypic integration and the evolution of signal repertoires: A case study of treefrog acoustic communication

Abstract

Animal signals are inherently complex phenotypes with many interacting parts combining to elicit responses from receivers. The pattern of interrelationships between signal components reflects the extent to which each component is expressed, and responds to selection, either in concert with or independently of others. Furthermore, many species have complex repertoires consisting of multiple signal types used in different contexts, and common morphological and physiological constraints may result in interrelationships extending across the multiple signals in species’ repertoires. The evolutionary significance of interrelationships between signal traits can be explored within the framework of phenotypic integration, which offers a suite of quantitative techniques to characterize complex phenotypes. In particular, these techniques allow for the assessment of modularity and integration, which describe, respectively, the extent to which sets of traits covary either independently or jointly. Although signal and repertoire complexity are thought to be major drivers of diversification and social evolution, few studies have explicitly measured the phenotypic integration of signals to investigate the evolution of diverse communication systems. We applied methods from phenotypic integration studies to quantify integration in the two primary vocalization types (advertisement and aggressive calls) in the treefrogs Hyla versicolor, Hyla cinerea, and Dendropsophus ebraccatus. We recorded male calls and calculated standardized phenotypic variance–covariance (P) matrices for characteristics within and across call types. We found significant integration across call types, but the strength of integration varied by species and corresponded with the acoustic similarity of the call types within each species. H. versicolor had the most modular advertisement and aggressive calls and the least acoustically similar call types. Additionally, P was robust to changing social competition levels in H. versicolor. Our findings suggest new directions in animal communication research in which the complex relationships among the traits of multiple signals are a key consideration for understanding signal evolution.

Natural selection acting on integrated phenotypes: covariance among functional leaf traits increases plant fitness

“…A second property of the phenotypic integration concept is the pattern of these correlations. The analysis of the patterns of phenotypic integration allows the detection of differences in trait association and fine‐scale relationships among traits, revealing the potential constraints acting on the independent evolution of different foliar functions (Reichert & Höbel, ). For example, a recent analysis of the functional strategies related to resource‐storage and acquisition during the domestication of wheat, detected that the number of significant correlations (a proxy of integration magnitude; Nicotra et al ., ) was greater in wild ancestors than in domesticated crops (Roucou et al ., ).…”

Specificity of Male Responses to Female Vibratory Signals in two Chinavia Species (Hemiptera: Pentatomidae) is Based on Signal Structure and Narrow Temporal Parameters

“…Our results show that male recognition and responses in both Chinavia species are based on integration of multiple components of female signals, including their different temporal characteristics, as well as their specific pulse train structure. The integrative evaluation of multiple components of signals and the specific responses of receivers to a narrow range of combinations of these components is also reported for chemical (Christensen, Hildebrand, Tomunson, & Doolitle, 1989), acoustic (von Helversen et al, 2004;Reichert & Höbel, 2018;Schul & Bush, 2002) and visual (Tibbetts, Mullen, & Dale, 2017) signals.…”

Measuring communicative complexity across modalities: a new framework in the context of the “social complexity hypothesis” and its application in true lemurs

“…I specifically argue for the interest of using a crossmodal network approach to signaling systems. This approach is based on the field of phenotypic integration, which aims at understanding the significance of the interrelationships and covariances between trait components (Reichert and Höbel 2018).…”

“…Within this approach, the response to selection on one characteristic of a given set of correlated characteristics is interpreted as depending on the strength and direction of selection acting on the other characteristics of this same set (Reichert and Höbel 2018). To some extent, signals within a repertoire may also be expected to covary positively or to be subject to conflicting selection pressures to optimize signaling in different contexts (Reichert and Höbel 2018). First, increasing the rate of a signal often entails increasing energetic expenditure leading to a trade-off in the expression of other signals.…”

“…First, increasing the rate of a signal often entails increasing energetic expenditure leading to a trade-off in the expression of other signals. Second, evolution may select for increased use of multi-component signals, the different components being at least partially under similar selective pressures; this will lead to increased correlations (Reichert and Höbel 2018). Hence, phenotypic integration techniques may help to improve the understanding of the causes and consequences of the evolution of multiple signals within a species repertoire (Reichert and Höbel 2018).…”