1. Department of Zoology, Department of Zoology, University of Agriculture, Faisalabad, Pakistan; javediqbal@gmail.com
2. Associate Professor; Department of Entomology, University of Agriculture, Faisalabad, Pakistan; sufiyanhamed34@uaf.edu.pk
3. Department of Zoology, Department of Zoology, University of Agriculture, Faisalabad, Pakistan; rasheedjahan78@gmail.com

*             Correspondence: khaliqaminhas3@gmail.com

Keywords: redundancy, modularity, multimodal, robustness, animal communication

1. INTRODUCTION

In order to interact with conspecifics and hetero-specifics in a range of situations and for a number of purposes, animals frequently employ complex signalling displays [1-3]. Though significant advancements have been made in the classification and formalisation of theories regarding the form and function of complex signals [4–8], our knowledge of how and why animals combine multiple distinct components within and across sensory modalities (multicomponent and multimodal signalling, respectively) is still in its infancy [9,10]. An evolutionary framework that allows for the analysis and comparison of entire signalling systems—an approach that takes into account various signalling traits, the intricate interactions among traits, and the structure-to-function relationships throughout—is a crucial missing component for the study of animal communication. In particular, there are few quantitative methods available for evaluating and analysing possible parallels and divergences in the architecture and operation of signalling systems. Our ability to identify broad trends and to develop and test evolutionary ideas is hampered by the absence of a common vocabulary and cohesive evolutionary framework. In light of this, we support using a systems approach in the study of animal communication. This approach takes into account the structure, organisation, and relationships between the various components of the signalling system, including how they may interact within and between contexts and how these interactions may alter over time [11]. Research on animal communication is still primarily concerned with (many) signal function(s) under a single circumstance. On the other hand, a systems approach supports the measurement and evaluation of the linkages between structure and function both inside and between circumstances (e.g., physiological state, time, receiver identity, or behavioural environment). While current theories of complex signalling are centred on signal function, regardless of its relationship with structure, systems theory and nomenclature are based on structure/function correlations. Animal communication research can build upon and borrow from an enormous body of knowledge and toolkit focused at understanding how and why systems function the way they do by embracing a paradigm that is more in line with systems biology. Crucially, it will also offer a common language and set of procedures that can make it easier to compare the architecture and functionality of systems across species and systems. Adjustments to our empirical approach (e.g., experimental design and data collection) as well as the deliberate integration and application of systems concepts, terminology, and analytical tools (and the possible development of new ones) will be necessary to refocus the field’s research focus to include structure/function relationships across conditions. We outline the current state of the subject and our proposal for integrating a systems approach to animal communication. By emphasising particular research that illustrate intersignal interactions and the dynamic character of animal signalling systems, we highlight the difficulty of fitting complex empirical data within the current categorization frameworks (2). An introduction to systems principles and related terminology follows this. After incorporating these ideas into a framework for animal communication, we quickly go over their evolutionary ramifications (3). After that, we offer recommendations for applying systems thinking to the study of animal communication, including methods and tools for comparing and visualising intricate signalling architectures and system component interactions (4). We provide a thorough case study of barn swallows to clarify the usefulness of such an approach. Finally, we address how new insights into animal communications as signal systems can further the field of animal communication research (5).

2. LITERATURE REVIEW

The early univariate models that examined situations in which there was only one signaller, one receiver, and one signal having a single purpose have largely been superseded in the study of animal communication [12,13]. It is noteworthy because it has broadened its scope to include a more inclusive perspective that recognises the significance of effective signal transmission as well as the receiver’s function, moving beyond selection for signal “content,” or information transfer. In fact, there is strong evidence presently available for the presence of manipulative signals and signaller–receiver conflict [14,15], and it is generally acknowledged that receivers play a key role in influencing how signals evolve (reviewed in [4,16–20]). Since signalling theory has revealed intricate relationships between floral signals and their pollinator targets, empirical and conceptual advancements in animal communication have even aided in the advancement of other research domains, such as plant-insect interactions [21–23]. A single function for a single signal was reflected in the first classification scheme for multimodal animal displays [5]. A number of follow-up frameworks centred on intersignal interactions and possible sources of selection on signals were developed in response to limitations of this approach, including the challenge of taking into account interactions between signal components and the potential for individual signals to have multiple functions [4,7,8,24]. Ground-dwelling spiders (reviewed in [25,26]), crustaceans (reviewed in [27]), anurans ([28], reviewed in [29]), insect pollinators (reviewed in [23,30]), birds [31,32], and primates [33,34] are just a few of the exceptional case studies of complex signalling that the field has since amassed. The understanding that the function(s) of the components of communication displays are not fixed has been brought about by the findings of these and other studies. Multidimensional animal communication can involve many receivers, receiver functions, components, methods, and sensory modalities [4, 8, 20]. Depending on the display composition (system architecture) or timeline, animal displays may operate differently. Wolf spiders, for instance, Schizocosa crassipes males, use a multimodal (visual and vibratory) courtship display [35, 36], with the visual component consisting of the dynamic waving of sexually dimorphic forelegs with prominent black brushes. Researchers have discovered that the presence or absence of the multicomponent vibratory display affects how the black brushes function. In particular, females react differently to different brush sizes only when the vibratory signal is present, as opposed to when it is not [37]. Thus, different display compositions (presence/absence of vibratory signal), the link between the intensity of a signal component (visible brush size) and the behavioural response (probability to mate) is varied; additionally, the vibratory signal interacts with a visual component (sensu [4]). Other wolf spiders have the same complicated signal component composition, environment, and receiver-dependent functions [38–42]. The male túngara frogs, Engystomops pustulosus, are known to exhibit functional interactions among signal components. Their complicated cries consist of a whine and occasionally a chuck. The temporal structure of whines and chucks affects female reactions, and calls that include both are more effective in drawing in females [43–45]. Female reactions are also influenced by the temporal synchronisation of the visual cues (visible expansion of a vocal sac) and auditory elements connected with calling [46]. Similar cross-modal interactions were discovered in research on Hyla squirella, the squirrel treefrog [47]. A comprehensive overview of further anuran signalling instances, such as those where element function is influenced by temporal coordination among signal elements, is given by Starnberger et al. [29]. Due to factors such as age, hormone profiles, past nutritional intake, and context-specific factors including context- or environment-specific context, individual receivers can differ in how they perceive and make decisions (reviewed in [19,48]). For instance, during the breeding season, female round gobies (Neogobius melanostomus) change how they react to unimodal versus multimodal male cues [49], while female wolf spiders (Rabida rabida) choose a mate based on both age and condition [50]. Female great bowerbirds are likely to see colours differently at the start of a male display bout than they do a minute into it, even within a single show [20]. Similar effects of a display’s social context can be seen in properties of the signal architecture itself as well as the functional response of receivers. When females are present as opposed to not, male pairs in the lance-tailed manakin, Chiroxiphia lanceolata, engage in more coordinated, predictable choreographed acrobatic performances [51, 52]. When a female is present vs absent during courtship displays, male wolf spiders exhibit similar variations in signal form [53]. On the other hand, the expression of male chemical signals in the Australian field cricket, Teleogryllus oceanicus, is contingent upon prior social experiences [54]. These case studies show how key interactions or variations among display components that are critical to system function may be overlooked by research efforts focused on matching individual signals to individual functions or individual receivers, at single time points and in unique settings. These examples demonstrate the growing trend towards more inclusive methods of animal communication. We propose that if we can include such methodologies and the accompanying data into a framework that facilitates cross-taxa/cross-study synthesis and hypothesis testing, then the impact will be genuinely tremendous. We suggest that studies of animal communication can benefit from adopting systems concepts like redundancy, degeneracy, pluripotentiality, and modularity [55]—essential organisational principles of complex biological as well as other (e.g., engineering) systems. These benefits extend beyond the effects of systems approaches on experimental design, data collection, and analyses. Important characteristics of these systems, like their resilience, adaptability, and—most importantly for biologically complex systems—evolvability, are influenced by these design principles. Redundancy gives a system a certain level of resilience [58]. Repetition of the redundant element can ensure that the signal continues to work in the event that it is lost (for example, if a call is muffled by background noise). For example, it is proposed that adults of the king penguin, Aptenodytes patagonicus, repeat similar syllables to counteract the masking effects of background noise in the colony [63]. However, this increased robustness only happens if the parts (in this case, syllables) work independently; repeated elements that are not independent do not easily fit into the redundancy notion of the system and may not ultimately increase system robustness. The evolutionary potential of the system is altered by redundancy [57,58]. The classic case of gene duplication serves as the greatest illustration of this phenomena. After duplication, one gene copy may experience a weakened state of selection, which could lead to the accumulation of mutations and eventually the adaptation of the duplicated gene for a new function [56, 64]. The multimodal vibratory and visual sexual display of male S. crassipes, or wolf spiders, has already been discussed [35,37,64,65] as an illustration of how interactions between signal elements and the overall signal composition can affect signal function; however, this species also offers a good example of signal degeneracy. Vibratory and visual components that can both support mate attraction are integrated, which reflects system degeneracy [37] and strengthens the display’s resistance to variations in light intensity or substrate characteristics. Because signal components may be susceptible to a variety of distinct selection pressures, pluripotentiality can also introduce evolutionary restrictions to the system. This is because any evolved modification may have several functional effects. As a result, it is proposed that similar production processes in aggressive cries and advertisements in the treefrog Dendropsophus ebraccatus constrain signal shape since different social situations have opposing selection pressures. Pluripotentiality may play a significant role in causing trade-offs within a single display component across contexts, while other studies support potential trade-offs between different signalling components within a single context [65]. Because of the connections between their structures or functions, integrated elements can be categorised. Due to their tight covariance [32] or repetition as a stereotyped unit in time or space [80], display components may be structurally grouped as a module. Certain notes, syllables, and phrases in a bird’s song, or distinct colour patches in a fish, are examples of structural modules in animal signalling; these elements are unlikely to be independent of other structures or elements, but they are likely related due to their shared physiological and developmental bases. Analyses and modularity concepts have already improved our comprehension of the complex and different displays of Parotia birds of paradise that are specific to individual lineages. Another extremely interesting way to visualise and quantify signalling dynamics is through signalling phenotype networks, partly because they can produce similar indices reflecting important aspects of system design for cross-system, cross-taxa comparisons. Though it has only lately been used in animal communication research, network thinking is widely used in studies addressing the evolution of integrated systems at the gene, protein, and ecological community level. A perspective of the signalling system’s overall architecture is made easier by transforming complex signal structure into signal phenotype networks. This process has led to the development of allied fields like phenotypic integration, where comparable techniques are now widely used. Wilkins et al.’s investigation of multimodal signalling in the North American barn swallow, Hirundo rustica erythrogaster, marked a significant advancement towards systems thinking. In the field, the research team measured 28 putative display components (two wings and 12 colour measurements; 14 measures of frequency, tempo, and repertoire per man) and gathered a wide range of phenotypic data from 50 males [32]. The produced phenotypic networks graphically illustrate the drawbacks of our conventional understanding of multimodal signal function. Strongly correlated groupings of signal components are categorised into structural modules (e.g., RL, RTmp, WTmp) in both scenarios. These modular components’ substantial covariance may indicate degeneracy (i.e., same information content that may reflect similar function but with different structures). This trend is consistent with content backup, a widely investigated theory in complex communication [63]. At the same time, different modules (or individual nodes) in the system are shown to share a common function by having predictable behavioural results. For instance, two different factors can best predict within-nest paternity [32]. The two modules/nodes in these examples share behavioural predictability, but they do not change, and so they probably do not share information content. This second situation lacks common information (lack of covariance between modules/nodes), yet it still shows degeneracy (shared function with diverse structure). Unlike the previous pattern of content backup, this pattern is directly tied to numerous messages, which is another well tested concept of complex signalling. Importantly, a systems approach highlights the reality that elements in a single display might perform several roles both within and between displays. Additionally, it serves as a helpful illustration of the need to avoid rigorously “binning” parts or displays into distinct categories, even when employing the language we support here, as this can restrict our comprehension of animal communication systems: A complicated signalling system could have components that are concurrently characterised by “multiple messages” and “content backup’’.

3. CONCLUSION

It is possible to view and study the intricate communication displays that occur amongst numerous animals as a system. Numerous levels of study are possible for this system, ranging from a single signaler/receiver to several signallers/receivers to interacting species in a community [97]. To find systems design principles and qualities, it will be necessary to investigate how signal components perform across contexts, including different signalling environments and changeable receivers. In addition, innovative experimental methods will continue to be crucial for comprehending signal interactions. We present a novel direction for future study that will adopt and modify similar ideas and instruments in order to adopt and align studies of animal signalling systems with other scientific disciplines. Readers are reoriented from the current signal-function method to an intuitive multidimensional/multifunctional approach through the use of a system approach, which provides a more accurate representation of animal communication. By incorporating systems thinking, experimental designs, methods, and terminology into the study of animal communication, signal design may be compared across taxa using a common vocabulary. By considering animal signals as dynamic systems, one can (i) generate testable evolutionary hypotheses that tackle patterns of system function and structure (like modularity and degeneracy) and how systems react to outside influences (like resilience and evolvability). It will (ii) result in the creation of novel analytical instruments and methodologies essential for the analysis of signalling systems and (iii) offer fresh perspectives on cross-contextual selection pressure, such as intra-versus intersexual selection. Additionally, systems approaches will (iv) provide a means of evaluating structure/function correlations both within and between modalities, allowing for the evaluation of the relative importance of modality-specific versus multimodal signals. Lastly, (v) by allowing for the possibility to evaluate and test systems design principles and properties in a comparative phylogenetic framework, a study of animal signals from a systems perspective will advance systems biology and allow for some of the first direct evolutionary tests of selection for systems design principles and properties.

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